• Case Studies of Database Management System (DBMS)

    Case Study 1: High-Frequency Trading System

    • Title: Ensuring Atomicity and Speed in High-Frequency Trading
    • Context:
      • High-frequency trading (HFT) systems execute a massive number of transactions in fractions of a second.
      • Data integrity and speed are paramount.
      • This case study examines how a specific HFT system manages transactions.
    • Key Concepts:
      • Transaction Processing Systems
      • Locking Mechanisms
      • Concurrency Related Problems
      • Logs and Checkpoints
    • Sections:
      • 1. Introduction to High-Frequency Trading
        • Explain HFT, its importance, and its challenges.
        • Describe the architecture of a typical HFT system.
      • 2. Transaction Processing in HFT
        • Detail the types of transactions involved (order placement, cancellation, etc.).
        • Explain the ACID properties (Atomicity, Consistency, Isolation, Durability) in the context of HFT.
      • 3. Concurrency Control
        • Discuss the concurrency challenges in HFT (e.g., multiple trades on the same stock).
        • Explain the locking mechanisms used (e.g., optimistic locking, fine-grained locking).
        • Analyze potential concurrency problems like race conditions and deadlocks, and how they are handled.
      • 4. Logging and Recovery
        • Describe the importance of transaction logs in HFT.
        • Explain how logs are used to recover from system failures.
        • Discuss checkpointing strategies to minimize recovery time.
      • 5. Performance Optimization
        • Analyze how the system is optimized for speed (e.g., in-memory databases, specialized hardware).
        • Discuss the trade-offs between speed and data integrity.
      • 6. Security Considerations
        • Outline the security threats in HFT (e.g., market manipulation).
        • Explain the security measures implemented to protect the system and data.
      • 7. Case Study Examples
        • Provide specific examples of HFT scenarios and how the database handles them.
        • Include code snippets or system diagrams if available.
      • 8. Challenges and Future Directions
        • Discuss the ongoing challenges in HFT database management.
        • Explore potential future technologies and solutions.
      • 9. Conclusion
        • Summarize the importance of robust transaction processing in HFT.
        • Highlight the key lessons learned from the case study.
    • Expansion:
      • Research specific HFT platforms (e.g., those used by major financial institutions).
      • Include performance benchmarks and metrics.
      • Analyze real-world HFT incidents and their database-related causes.

    Case Study 2: Global Banking System

    • Title: Managing Distributed Transactions in a Global Banking Network
    • Context:
      • Modern banks operate across multiple countries with data spread across various servers.
      • Ensuring consistency and reliability in this distributed environment is critical.
    • Key Concepts:
      • Distributed Databases
      • Transaction Processing Systems
      • Concurrency Related Problems
      • Logs and Checkpoints
    • Sections:
      • 1. Overview of Global Banking Systems
        • Describe the architecture of a global banking network.
        • Explain the need for distributed databases in this context.
      • 2. Distributed Database Architecture
        • Discuss different distributed database architectures (e.g., homogeneous, heterogeneous).
        • Explain data fragmentation and replication strategies.
      • 3. Distributed Transactions
        • Describe the challenges of managing transactions across multiple databases.
        • Explain the concept of global transactions and their properties.
      • 4. Concurrency Control in Distributed Systems
        • Discuss concurrency control protocols for distributed databases (e.g., two-phase commit, three-phase commit).
        • Analyze potential concurrency problems like distributed deadlocks.
      • 5. Logging and Recovery in Distributed Databases
        • Explain how logs and checkpoints are used in distributed systems.
        • Discuss recovery strategies for distributed transactions.
      • 6. Security in Global Banking Systems
        • Outline the security challenges, including data breaches, fraud, and regulatory compliance.
        • Describe security measures like encryption, access control, and auditing.
      • 7. Case Study Examples
        • Provide examples of typical banking transactions (e.g., international transfers, foreign exchange).
        • Illustrate how these transactions are handled in a distributed environment.
      • 8. Challenges and Future Trends
        • Discuss the challenges of maintaining consistency and performance in global banking systems.
        • Explore emerging trends like blockchain and their potential impact.
      • 9. Conclusion
        • Summarize the complexities of managing distributed transactions in global banking.
        • Highlight the importance of robust database systems for the financial industry.
    • Expansion:
      • Research specific global banking networks (e.g., SWIFT).
      • Analyze the impact of regulations like GDPR on data management.
      • Include case studies of major banking outages and their causes.

    Case Study 3: E-commerce Platform

    • Title: Scaling Transaction Processing for a High-Volume E-commerce Platform
    • Context:
      • E-commerce platforms like Amazon or eBay handle millions of transactions daily.
      • Scalability, reliability, and data consistency are crucial.
    • Key Concepts:
      • Transaction Processing Systems
      • Locking Mechanisms
      • Concurrency Related Problems
      • Normalization
    • Sections:
      • 1. Overview of E-commerce Platforms
        • Describe the architecture of a typical e-commerce platform.
        • Explain the different types of transactions involved (e.g., browsing, adding to cart, checkout).
      • 2. Transaction Management
        • Analyze the transaction processing requirements of an e-commerce platform.
        • Discuss the importance of ACID properties in this context.
      • 3. Concurrency Control
        • Explain the concurrency challenges (e.g., multiple users accessing the same product).
        • Discuss locking mechanisms like optimistic and pessimistic locking.
        • Analyze how concurrency control affects performance and user experience.
      • 4. Database Design and Normalization
        • Explain the importance of proper database design for scalability.
        • Discuss the role of normalization in reducing data redundancy and improving performance.
        • Provide examples of database schemas for e-commerce platforms.
      • 5. Scalability and Performance
        • Analyze techniques for scaling e-commerce databases (e.g., sharding, replication).
        • Discuss performance optimization strategies (e.g., caching, query optimization).
      • 6. Security Considerations
        • Outline the security threats (e.g., SQL injection, cross-site scripting).
        • Describe security measures to protect customer data and transactions.
      • 7. Case Study Examples
        • Provide examples of specific e-commerce scenarios (e.g., flash sales, Black Friday).
        • Illustrate how the database handles these high-volume events.
      • 8. Challenges and Future Trends
        • Discuss the challenges of managing ever-increasing transaction volumes.
        • Explore emerging trends like NoSQL databases and their suitability for e-commerce.
      • 9. Conclusion
        • Summarize the critical role of database systems in e-commerce.
        • Highlight the importance of scalability, reliability, and security.
    • Expansion:
      • Research specific e-commerce platforms and their database technologies.
      • Analyze the impact of cloud computing on e-commerce databases.
      • Include performance benchmarks and case studies of successful scaling efforts.

    Case Study 4: Social Media Network

    >

    • Title: Ensuring Data Consistency and Availability in a Social Media Network
    • Context:
      • Social media networks like Facebook or Twitter store and process massive amounts of user-generated data.
      • High availability and data consistency are essential for a positive user experience.
    • Key Concepts:
      • Distributed Databases
      • Concurrency Related Problems
      • Logs and Checkpoints
      • Normalization
    • Sections:
      • 1. Overview of Social Media Networks
        • Describe the architecture of a typical social media network.
        • Explain the different types of data stored (e.g., profiles, posts, connections).
      • 2. Distributed Database Architecture
        • Discuss the reasons for using distributed databases in social media.
        • Explain data partitioning and replication strategies.
      • 3. Concurrency Control
        • Analyze the concurrency challenges in social media (e.g., multiple users updating the same profile).
        • Discuss different concurrency control mechanisms, including optimistic concurrency control.
      • 4. Data Consistency and Availability
        • Explain the trade-offs between data consistency and availability in distributed systems.
        • Discuss consistency models (e.g., eventual consistency, strong consistency).
      • 5. Logging and Recovery
        • Describe the role of logs and checkpoints in ensuring data durability.
        • Explain how the system recovers from failures without losing data.
      • 6. Database Design and Normalization
        • Discuss the database schema used to store social media data.
        • Explain how normalization principles are applied.
      • 7. Case Study Examples
        • Provide examples of specific social media features (e.g., timeline updates, friend requests).
        • Illustrate how the database handles these operations in a distributed environment.
      • 8. Challenges and Future Trends
        • Discuss the challenges of managing the explosive growth of social media data.
        • Explore emerging trends like graph databases and their suitability for social networks.
      • 9. Conclusion
        • Summarize the database requirements of social media networks.
        • Highlight the importance of scalability, consistency, and availability.
    • Expansion:
      • Research specific social media platforms and their database architectures.
      • Analyze the use of caching and other performance optimization techniques.
      • Include case studies of social media outages and their impact.

    Case Study 5: Healthcare Record System

    • Title: Ensuring Security and Integrity in a Healthcare Record System
    • Context:
      • Healthcare systems store sensitive patient data that must be protected.
      • Security, privacy, and data integrity are of utmost importance.
    • Key Concepts:
      • Security Issues
      • Cell-Based Security
      • Transaction Processing Systems
      • Logs and Checkpoints
    • Sections:
      • 1. Overview of Healthcare Record Systems
        • Describe the architecture of a typical electronic health record (EHR) system.
        • Explain the types of data stored (e.g., patient demographics, medical history, prescriptions).
      • 2. Security Requirements
        • Discuss the legal and ethical requirements for protecting patient data (e.g., HIPAA).
        • Outline the security threats (e.g., unauthorized access, data breaches).
      • 3. Cell-Based Security
        • Explain the concept of cell-based security and how it can be used to protect sensitive data.
        • Provide examples of how cell-level access controls can be implemented in an EHR system.
      • 4. Transaction Processing
        • Analyze the transaction processing requirements of an EHR system.
        • Discuss the importance of ACID properties, especially atomicity and durability.
      • 5. Logging and Auditing
        • Explain the importance of detailed logs for tracking data access and modifications.
        • Discuss how logs can be used for auditing and compliance purposes.
      • 6. Data Integrity
        • Describe the measures taken to ensure data integrity (e.g., data validation, checksums).
        • Discuss how the system prevents data corruption and loss.
      • 7. Case Study Examples
        • Provide examples of security breaches in healthcare and their consequences.
        • Illustrate how cell-based security could have mitigated these breaches.
      • 8. Challenges and Future Trends
        • Discuss the challenges of balancing data accessibility with security.
        • Explore emerging technologies like blockchain for secure data sharing.
      • 9. Conclusion
        • Summarize the security and integrity requirements of healthcare record systems.
        • Highlight the importance of robust database systems for protecting patient data.
    • Expansion:
      • Research specific EHR systems and their security features.
      • Analyze the impact of regulations like HIPAA on database design.
      • Include case studies of insider threats and how they are addressed.

    Case Study 6: Supply Chain Management System

    • Title: Tracking Products and Transactions Across a Distributed Supply Chain
    • Context:
      • Supply chains involve multiple parties (suppliers, manufacturers, distributors, retailers) with data spread across different systems.
      • Visibility, traceability, and data consistency are crucial for efficient supply chain management.
    • Key Concepts:
      • Distributed Databases
      • Transaction Processing Systems
      • Concurrency Related Problems
      • Security Issues
    • Sections:
      • 1. Overview of Supply Chain Management
        • Describe the flow of goods and information in a typical supply chain.
        • Explain the need for sharing data across different organizations.
      • 2. Distributed Database Architecture
        • Discuss the challenges of integrating data from disparate systems.
        • Explain different approaches to distributed databases in supply chains (e.g., federated databases).
      • 3. Transaction Processing
        • Analyze the types of transactions involved (e.g., orders, shipments, invoices).
        • Discuss the importance of ACID properties in supply chain transactions.
      • 4. Concurrency Control
        • Explain the concurrency challenges (e.g., multiple parties updating inventory levels).
        • Discuss how concurrency control mechanisms ensure data consistency.
      • 5. Security and Data Sharing
        • Outline the security risks (e.g., unauthorized access to sensitive information).
        • Describe security measures for protecting data shared across the supply chain.
      • 6. Data Visibility and Traceability
        • Explain how distributed databases enable tracking products and transactions.
        • Discuss the benefits of improved visibility for supply chain efficiency.
      • 7. Case Study Examples
        • Provide examples of specific supply chain scenarios (e.g., tracking a product from origin to consumer).
        • Illustrate how distributed databases facilitate data sharing and collaboration.
      • 8. Challenges and Future Trends
        • Discuss the challenges of achieving seamless data integration across the supply chain.
        • Explore emerging technologies like blockchain for enhancing transparency and security.
      • 9. Conclusion
        • Summarize the role of distributed databases in supply chain management.
        • Highlight the importance of data sharing, security, and traceability.
    • Expansion:
      • Research specific supply chain management systems and their underlying databases.
      • Analyze the use of EDI (Electronic Data Interchange) and APIs for data exchange.
      • Include case studies of supply chain disruptions and how data management played a role.

    Case Study 7: Telecommunications Billing System

    • Title: Handling High-Volume Transactions in a Telecommunications Billing System
    • Context:
      • Telecommunications companies process millions of call records and billing events daily.
      • Accuracy, reliability, and scalability are essential for billing integrity.
    • Key Concepts:
      • Transaction Processing Systems
      • Locking Mechanisms
      • Concurrency Related Problems
      • Logs and Checkpoints
    • Sections:
      • 1. Overview of Telecommunications Billing Systems
        • Describe the architecture of a typical telecommunications billing system.
        • Explain the types of data processed (e.g., call detail records, usage data, customer information).
      • 2. Transaction Management
        • Analyze the transaction processing requirements of a billing system.
        • Discuss the importance of ACID properties, especially accuracy and durability.
      • 3. Concurrency Control
        • Explain the concurrency challenges (e.g., multiple processes updating customer accounts).
        • Discuss locking mechanisms and their impact on billing performance.
      • 4. Data Accuracy and Integrity
        • Describe the measures taken to ensure the accuracy of billing data.
        • Discuss data validation and error handling mechanisms.
      • 5. Logging and Recovery
        • Explain the importance of logs and checkpoints for recovering from billing errors or system failures.
        • Discuss how logs are used to ensure that all billing events are processed correctly.
      • 6. Scalability and Performance
        • Analyze techniques for scaling billing databases to handle high transaction volumes.
        • Discuss performance optimization strategies.
      • 7. Case Study Examples
        • Provide examples of specific billing scenarios (e.g., calculating charges for different call types, applying discounts).
        • Illustrate how the database handles these operations.
      • 8. Challenges and Future Trends
        • Discuss the challenges of managing the increasing complexity of billing (e.g., bundled services, dynamic pricing).
        • Explore emerging trends like real-time billing and their database requirements.
      • 9. Conclusion
        • Summarize the database requirements of telecommunications billing systems.
        • Highlight the importance of accuracy, reliability, and scalability.
    • Expansion:
      • Research specific telecommunications companies and their billing systems.
      • Analyze the impact of regulations on billing data management.
      • Include case studies of billing errors and their consequences.

    Case Study 8: Online Gaming Platform

    >

    • Title: Managing Real-Time Data and Transactions in an Online Gaming Platform
    • Context:
      • Online gaming platforms handle a large number of concurrent users and real-time interactions.
      • Low latency, high throughput, and data consistency are crucial for a smooth gaming experience.
    • Key Concepts:
      • Transaction Processing Systems
      • Concurrency Related Problems
      • Distributed Databases
      • Normalization
    • Sections:
      • 1. Overview of Online Gaming Platforms
        • Describe the architecture of a typical online gaming platform.
        • Explain the types of data stored (e.g., player profiles, game state, inventory).
      • 2. Real-Time Data Management
        • Discuss the challenges of managing real-time data updates (e.g., player movements, game events).
        • Explain the need for low-latency database operations.
      • 3. Concurrency Control
        • Analyze the concurrency challenges in online gaming (e.g., multiple players interacting with the same game object).
        • Discuss different concurrency control mechanisms, including optimistic concurrency control and techniques for minimizing latency.
      • 4. Distributed Databases
        • Explain how distributed databases are used to handle a large number of concurrent users.
        • Discuss data sharding and replication strategies for online games.
      • 5. Database Design and Normalization
        • Discuss the database schema used to store game data.
        • Explain how normalization principles are applied to optimize performance.
      • 6. Scalability and Performance
        • Analyze techniques for scaling gaming databases to handle a large number of concurrent players.
        • Discuss performance optimization strategies, such as caching and in-memory databases.
      • 7. Case Study Examples
        • Provide examples of specific game scenarios (e.g., player battles, item trading).
        • Illustrate how the database handles these real-time interactions.
      • 8. Challenges and Future Trends
        • Discuss the challenges of managing the increasing complexity of online games.
        • Explore emerging trends like cloud gaming and their database requirements.
      • 9. Conclusion
        • Summarize the database requirements of online gaming platforms.
        • Highlight the importance of low latency, high throughput, and data consistency.
    • Expansion:
      • Research specific online games and their database technologies.
      • Analyze the use of NoSQL databases for online gaming.
      • Include case studies of game server outages and their impact.

    Case Study 9: Smart City Infrastructure

    • Title: Securing and Managing Data in a Smart City Infrastructure
    • Context:
      • Smart cities collect and process vast amounts of data from various sources (sensors, devices, systems).
      • Security, privacy, and data management are critical for the success of smart city initiatives.
    • Key Concepts:
      • Security Issues
      • Cell-Based Security
      • Distributed Databases
      • Logs and Checkpoints
    • Sections:
      • 1. Overview of Smart City Infrastructure
        • Describe the components of a typical smart city (e.g., sensors, networks, data centers).
        • Explain the types of data collected (e.g., traffic, environmental, public safety).
      • 2. Data Management Challenges
        • Discuss the challenges of collecting, storing, and processing large volumes of data from diverse sources.
        • Explain the need for a distributed database architecture.
      • 3. Security and Privacy
        • Outline the security threats in a smart city (e.g., data breaches, cyberattacks).
        • Discuss the privacy concerns related to collecting and using personal data.
      • 4. Cell-Based Security
        • Explain how cell-based security can be used to protect sensitive data in a smart city.
        • Provide examples of how cell-level access controls can be implemented for different types of data.
      • 5. Distributed Databases
        • Discuss the use of distributed databases to manage data from various sources.
        • Explain data aggregation and integration strategies.
      • 6. Logging and Auditing
        • Describe the importance of logs for tracking data access and usage.
        • Discuss how logs can be used for auditing and compliance purposes.
      • 7. Case Study Examples
        • Provide examples of specific smart city applications (e.g., intelligent traffic management, public safety).
        • Illustrate how data is collected, processed, and secured in these applications.
      • 8. Challenges and Future Trends
        • Discuss the challenges of ensuring data security and privacy in a complex smart city environment.
        • Explore emerging technologies like edge computing and their impact on data management.
      • 9. Conclusion
        • Summarize the data management requirements of smart city infrastructure.
        • Highlight the importance of security, privacy, and scalability.
    • Expansion:
      • Research specific smart city projects and their data management systems.
      • Analyze the impact of IoT (Internet of Things) on smart city data.
      • Include case studies of security breaches in smart cities and their consequences.

    Case Study 10: Content Management System

    • Title: Ensuring Data Consistency and Efficient Retrieval in a Content Management System
    • Context:
      • Content management systems (CMS) like WordPress or Drupal store and manage various types of digital content.
      • Data consistency, efficient retrieval, and scalability are crucial for a good user experience.
    • Key Concepts:
      • Normalization
      • Transaction Processing Systems
      • Locking Mechanisms
      • Concurrency Related Problems
    • Sections:
      • 1. Overview of Content Management Systems
        • Describe the architecture of a typical CMS.
        • Explain the types of content stored (e.g., articles, images, videos).
      • 2. Database Design and Normalization
        • Explain the importance of proper database design for efficient content retrieval.
        • Discuss the role of normalization in reducing data redundancy and improving query performance.
        • Provide examples of database schemas for CMS.
      • 3. Transaction Processing
        • Analyze the transaction processing requirements of a CMS (e.g., creating, editing, publishing content).
        • Discuss the importance of ACID properties, especially consistency and durability.
      • 4. Locking Mechanisms
        • Explain the concurrency challenges in a CMS (e.g., multiple users editing the same article).
        • Discuss locking mechanisms like optimistic and pessimistic locking.
        • Analyze how concurrency control affects performance and data consistency.
      • 5. Caching and Performance Optimization
        • Discuss the use of caching to improve content retrieval performance.
        • Explain other performance optimization strategies (e.g., query optimization, indexing).
      • 6. Scalability
        • Analyze techniques for scaling CMS databases to handle a large number of users and content.
        • Discuss database sharding and replication in the context of CMS.
      • 7. Case Study Examples
        • Provide examples of specific CMS scenarios (e.g., a high-traffic blog, an e-learning platform).
        • Illustrate how the database handles content creation, editing, and retrieval.
      • 8. Challenges and Future Trends
        • Discuss the challenges of managing the increasing volume and complexity of digital content.
        • Explore emerging trends like headless CMS and their database requirements.
      • 9. Conclusion
        • Summarize the database requirements of content management systems.
        • Highlight the importance of efficient retrieval, data consistency, and scalability.
    • Expansion:
      • Research specific CMS platforms (e.g., WordPress, Drupal) and their database technologies.
      • Analyze the use of NoSQL databases for content storage.
      • Include performance benchmarks and case studies of high-traffic websites.

    Case Studies of Software Engineering (SE)

    Case Study 1: Microservices Architecture for an E-commerce Platform

    Title

    Decomposing a Monolithic E-commerce Application into Microservices

    Context

    A large e-commerce company is migrating from a monolithic architecture to a microservices architecture to improve scalability, maintainability, and fault tolerance.

    Key Concepts
    • Cohesion
    • Coupling
    Sections
    1. Introduction:

      • Describe the monolithic architecture of the e-commerce platform.
      • Explain the challenges (scalability, deployment, etc.) of the monolithic architecture.
    2. Microservices Design:

      • Explain the principles of microservices.
      • Describe how the e-commerce application is decomposed into services (e.g., product catalog, order management, user authentication).
      • Analyze the cohesion within each microservice.
      • Analyze the coupling between microservices (using diagrams and examples).
    3. Implementation:

      • Discuss the technologies used (e.g., Docker, Kubernetes, APIs).
      • Explain how data consistency is maintained across services.
    4. Testing:

      • Describe the testing strategy, including unit tests, integration tests, and system tests.
      • Explain how the distributed nature of microservices affects testing.
    5. Deployment:

      • Discuss the deployment process, including continuous integration and continuous deployment (CI/CD).
      • Explain how services are deployed independently.
    6. Monitoring and Scaling:

      • Describe how the microservices are monitored.
      • Explain how the system is scaled to handle increased traffic.
    7. Benefits and Challenges:

      • Analyze the benefits of the microservices architecture (e.g., improved scalability, faster development).
      • Discuss the challenges (e.g., increased complexity, distributed transactions).
    8. Metrics:

      • Define and collect relevant project and process metrics.
      • Analyze how metrics such as deployment frequency, mean time to recovery, and service latency are tracked and improved.
    9. Conclusion:

      • Summarize the results of the migration to microservices.
      • Discuss the lessons learned and best practices.
    Expansion
    • Compare different service discovery mechanisms.
    • Analyze the impact of microservices on team organization.

    Case Study 2: Developing a Mobile Banking Application

    Title

    Cost Estimation and Feasibility Analysis for a Mobile Banking App

    Context

    A bank wants to develop a mobile application to allow customers to access their accounts, make transactions, and manage their finances.

    Key Concepts
    • COCOMO Model
    • Feasibility Analysis
    Sections
    1. Introduction:

      • Describe the purpose and features of the mobile banking application.
      • Explain the project goals and constraints.
    2. Feasibility Analysis:

      • Technical Feasibility:
        • Assess the technical requirements (e.g., mobile platforms, security, integration with core banking systems).
        • Evaluate the availability of technology and expertise.
      • Economic Feasibility:
        • Estimate the development costs, including hardware, software, and personnel.
        • Perform a cost-benefit analysis.
      • Operational Feasibility:
        • Assess whether the application will meet the needs of the bank and its customers.
        • Evaluate the impact on existing processes and workflows.
      • Schedule Feasibility:
        • Estimate the project timeline and assess whether it can be completed within the desired timeframe.
      • Legal Feasibility:
        • Analyze legal and regulatory requirements (e.g., data privacy, security standards).
    3. COCOMO Model Application:

      • Estimate the size of the application (e.g., lines of code, function points).
      • Apply the COCOMO model (basic, intermediate, or detailed) to estimate effort, cost, and schedule.
      • Justify the choice of COCOMO parameters.
      • Perform sensitivity analysis to understand how different factors affect the estimates.
    4. Risk Assessment:

      • Identify potential risks (e.g., security vulnerabilities, integration issues, changing requirements).
      • Analyze the likelihood and impact of each risk.
      • Develop a risk management plan.
    5. Project Planning:

      • Outline the project plan, including phases, activities, and milestones.
      • Define the project deliverables and acceptance criteria.
    6. Metrics:

      • Identify key project metrics to track progress and performance (e.g., planned vs. actual effort, schedule variance).
      • Define process metrics to measure the efficiency and effectiveness of the development process (e.g., defect density, code review coverage).
    7. Conclusion:

      • Summarize the findings of the feasibility analysis and COCOMO estimation.
      • Make recommendations regarding project approval and execution.
    Expansion
    • Compare the COCOMO estimates with other estimation techniques.
    • Discuss the challenges of estimating the cost of mobile application development.

    Case Study 3: Developing a Real-Time Stock Trading Platform

    Title

    Ensuring Low Coupling and High Cohesion in a Real-Time Stock Trading Platform

    Context

    A financial company is developing a platform that allows users to trade stocks in real-time. Low latency and high reliability are critical.

    Key Concepts
    • Cohesion
    • Coupling
    Sections
    1. Introduction:

      • Describe the requirements of the stock trading platform.
      • Explain the importance of low latency and high reliability.
    2. System Architecture:

      • Describe the architecture of the platform, including the key components (e.g., order management, market data, trade execution).
      • Explain how the system handles concurrent transactions.
    3. Module Design:

      • Analyze the modules in the system and their responsibilities.
      • Evaluate the cohesion within each module.
      • Evaluate the coupling between modules.
    4. Design Patterns:

      • Discuss the design patterns used to achieve low coupling and high cohesion (e.g., Observer, Mediator).
      • Explain how these patterns improve the maintainability and flexibility of the system.
    5. Technology Stack:

      • Describe the technologies used to develop the platform (e.g., programming languages, databases, messaging systems).
      • Explain how these technologies support low coupling and high cohesion.
    6. Testing:

      • Describe the testing strategy, including unit tests, integration tests, and performance tests.
      • Explain how the system is tested for latency and reliability.
    7. Deployment:

      • Discuss the deployment process, including how the system is deployed to a production environment.
      • Explain how updates are deployed without disrupting trading activity.
    8. Metrics:

      • Identify project and process metrics relevant to real-time trading systems.
      • Examples: transaction processing time, order execution success rate, system uptime.
    9. Conclusion:

      • Summarize how low coupling and high cohesion contribute to the success of the platform.
      • Discuss the lessons learned and best practices.
    Expansion
    • Analyze the use of message queues for decoupling components.
    • Discuss the challenges of maintaining data consistency in a distributed trading system.

    Case Study 4: Implementing a New ERP System

    Title

    Feasibility Analysis and Project Management for ERP System Implementation

    Context

    A manufacturing company is implementing a new Enterprise Resource Planning (ERP) system to integrate its business processes.

    Key Concepts
    • Feasibility Analysis
    • Project and Process Metrics
    Sections
    1. Introduction:

      • Describe the company’s existing systems and the need for an ERP system.
      • Explain the goals of the ERP implementation project.
    2. Feasibility Analysis:

      • Technical Feasibility:
        • Evaluate the technical requirements, including hardware, software, and network infrastructure.
        • Assess the compatibility of the ERP system with existing systems.
      • Economic Feasibility:
        • Estimate the costs, including software licenses, implementation services, training, and ongoing maintenance.
        • Perform a cost-benefit analysis, considering both tangible and intangible benefits.
      • Operational Feasibility:
        • Assess the impact on the company’s organizational structure, business processes, and employee roles.
        • Evaluate user acceptance and readiness for change.
      • Schedule Feasibility:
        • Estimate the project timeline, considering the complexity of the implementation and the company’s resources.
      • Legal Feasibility:
        • Ensure compliance with relevant regulations and standards.
    3. Project Management:

      • Describe the project management approach used (e.g., Waterfall, Agile).
      • Outline the project plan, including phases, activities, milestones, and deliverables.
      • Discuss how the project is organized, staffed, and managed.
    4. Metrics:

      • Define key project metrics to track progress, cost, and schedule (e.g., earned value, cost variance, schedule variance).
      • Establish process metrics to measure the quality and efficiency of the implementation process (e.g., number of defects, user training effectiveness).
    5. Change Management:

      • Explain the change management strategies used to ensure smooth adoption of the new system.
      • Discuss how employee resistance is addressed.
    6. Risk Management:

      • Identify potential risks (e.g., scope creep, budget overruns, data migration issues).
      • Analyze the likelihood and impact of each risk.
      • Develop a risk management plan.
    7. Post-Implementation Review:

      • Evaluate the success of the ERP implementation.
      • Analyze the project outcomes against the initial goals and objectives.
      • Identify lessons learned and best practices.
    8. Conclusion:

      • Summarize the key factors that contributed to the success or failure of the ERP implementation.
      • Provide recommendations for future ERP projects.
    Expansion
    • Compare different ERP systems (e.g., SAP, Oracle, Microsoft Dynamics).
    • Discuss the role of consultants in ERP implementations.

    Case Study 5: Developing a Social Media Analytics Platform

    Title

    Designing a Scalable and Maintainable Social Media Analytics Platform

    Context

    A company is developing a platform to collect, process, and analyze data from social media websites.

    Key Concepts
    • Cohesion
    • Coupling
    Sections
    1. Introduction:

      • Describe the purpose of the social media analytics platform.
      • Explain the types of data collected and the analyses performed.
    2. System Architecture:

      • Describe the architecture of the platform, including the key components (e.g., data collection, data processing, data storage, data visualization).
      • Explain how the system handles large volumes of data.
    3. Module Design:

      • Analyze the modules in the system and their responsibilities.
      • Evaluate the cohesion within each module.
      • Evaluate the coupling between modules.
    4. Scalability and Maintainability:

      • Discuss how the architecture and design of the platform support scalability and maintainability.
      • Explain the design principles and patterns used to achieve these goals.
    5. Technology Stack:

      • Describe the technologies used to develop the platform (e.g., programming languages, databases, big data technologies).
      • Explain how these technologies support scalability and maintainability.
    6. Testing:

      • Describe the testing strategy, including unit tests, integration tests, and performance tests.
      • Explain how the system is tested for data accuracy and scalability.
    7. Deployment:

      • Discuss the deployment process, including how the platform is deployed to a production environment.
      • Explain how updates are deployed without disrupting data collection and analysis.
    8. Metrics:

      • Define project metrics like time to market and budget adherence.
      • Define process metrics like data ingestion rate, query response time, and system uptime.
    9. Conclusion:

      • Summarize how cohesion and coupling influenced the design of the platform.
      • Discuss the lessons learned and best practices.
    Expansion
    • Analyze the use of message queues and distributed computing frameworks.
    • Discuss the challenges of ensuring data quality and accuracy in social media analytics.

    Case Study 6: Modernizing a Legacy System

    Title

    Cost Estimation and Risk Management for Legacy System Modernization

    Context

    A financial institution is modernizing a legacy system that is critical to its operations.

    Key Concepts
    • COCOMO Model
    • Project and Process Metrics
    Sections
    1. Introduction:

      • Describe the legacy system and its limitations.
      • Explain the goals of the modernization project.
    2. Feasibility Analysis:

      • Discuss the technical, economic, operational, and schedule feasibility of the modernization project.
    3. COCOMO Model Application:

      • Estimate the size of the system to be modernized.
      • Apply the COCOMO model to estimate the effort, cost, and schedule for the modernization project.
      • Discuss the factors that affect the cost of modernization (e.g., code complexity, level of documentation).
    4. Risk Management:

      • Identify potential risks (e.g., data migration issues, integration problems, lack of documentation).
      • Analyze the likelihood and impact of each risk.
      • Develop a risk management plan.
    5. Project Planning:

      • Outline the project plan, including phases, activities, and milestones.
      • Define the project deliverables and acceptance criteria.
    6. Metrics:

      • Define project metrics (e.g., budget variance, schedule adherence).
      • Define process metrics (e.g., code migration rate, testing efficiency).
    7. Migration Strategy:

      • Discuss the strategy for migrating from the legacy system to the new system (e.g., phased migration, parallel migration).
      • Explain how data migration is handled.
    8. Testing:

      • Describe the testing strategy, including unit tests, integration tests, and system tests.
      • Explain how the modernized system is tested for functionality, performance, and security.
    9. Conclusion:

      • Summarize the cost estimation and risk management activities.
      • Discuss the lessons learned and best practices for legacy system modernization.
    Expansion
    • Compare different modernization approaches (e.g., re-writing, re-engineering, replacing).
    • Discuss the challenges of modernizing systems with poor documentation.

    Case Study 7: Developing a High-Performance Computing Application

    Title

    Designing for Performance and Scalability in a High-Performance Computing Application

    Context

    A research institution is developing a software application to simulate complex scientific phenomena on a high-performance computing (HPC) cluster.

    Key Concepts
    • Cohesion
    • Coupling
    Sections
    1. Introduction:

      • Describe the purpose of the HPC application and the scientific problem it addresses.
      • Explain the performance and scalability requirements.
    2. System Architecture:

      • Describe the architecture of the application, including the key components and how they are distributed across the HPC cluster.
      • Explain the parallel programming model used (e.g., MPI, OpenMP).
    3. Module Design:

      • Analyze the modules in the application and their responsibilities.
      • Evaluate the cohesion within each module.
      • Evaluate the coupling between modules.
    4. Performance Optimization:

      • Discuss the techniques used to optimize the performance of the application (e.g., algorithm selection, data structures, memory management).
      • Explain how the application is optimized for parallel execution.
    5. Scalability:

      • Discuss how the architecture and design of the application support scalability.
      • Explain how the application can be scaled to run on larger HPC clusters.
    6. Testing:

      • Describe the testing strategy, including unit tests, integration tests, and performance tests.
      • Explain how the application is tested for correctness, performance, and scalability.
    7. Deployment:

      • Describe the deployment process, including how the application is deployed on the HPC cluster.
      • Explain how the application is configured and managed in the HPC environment.
    8. Metrics:

      • Define metrics like speedup, efficiency, and scalability.
      • Include resource utilization metrics (CPU, memory, network).
    9. Conclusion:

      • Summarize how cohesion and coupling influenced the design of the application.
      • Discuss the lessons learned and best practices for developing HPC applications.
    Expansion
    • Analyze the use of specific HPC libraries and tools.
    • Discuss the challenges of debugging and profiling parallel applications.

    Case Study 8: Implementing a New Healthcare System

    Title

    Feasibility Analysis and Risk Management for a Healthcare System Implementation

    Context

    A hospital is implementing a new healthcare system to manage patient records, appointments, and billing.

    Key Concepts
    • Feasibility Analysis
    • Project and Process Metrics
    Sections
    1. Introduction:

      • Describe the hospital’s existing systems and the need for a new healthcare system.
      • Explain the goals of the implementation project.
    2. Feasibility Analysis:

      • Technical Feasibility:
        • Evaluate the technical requirements, including hardware, software, and network infrastructure.
        • Assess the compatibility of the new system with existing systems.
      • Economic Feasibility:
        • Estimate the costs, including software licenses, implementation services, training, and ongoing maintenance.
        • Perform a cost-benefit analysis.
      • Operational Feasibility:
        • Assess the impact on the hospital’s workflows, staff roles, and patient care processes.
        • Evaluate user acceptance and readiness for change.
      • Schedule Feasibility:
        • Estimate the project timeline, considering the complexity of the implementation and the hospital’s resources.
      • Legal Feasibility:
        • Ensure compliance with relevant regulations (e.g., HIPAA).
    3. Risk Management:

      • Identify potential risks (e.g., data migration issues, integration problems, user resistance).
      • Analyze the likelihood and impact of each risk.
      • Develop a risk management plan.
    4. Project Planning:

      • Outline the project plan, including phases, activities, and milestones.
      • Define the project deliverables and acceptance criteria.
    5. Metrics:

      • Define project metrics like on-time completion and budget adherence.
      • Define process metrics like data migration accuracy, user training completion rate, and system uptime.
    6. Change Management:

      • Explain the change management strategies used to ensure smooth adoption of the new system.
      • Discuss how to address concerns from medical staff and other users.
    7. Testing:

      • Describe the testing strategy, including unit tests, integration tests, and user acceptance testing.
      • Explain how the system is tested for functionality, performance, security, and usability in a healthcare setting.
    8. Conclusion:

      • Summarize the feasibility analysis and risk management activities.
      • Discuss the key factors for successful healthcare system implementation.
    Expansion
    • Discuss the specific challenges of implementing healthcare systems.
    • Analyze the impact of electronic health records on patient care and data security.

    Case Study 9: Developing an Autonomous Vehicle Control System

    Title

    Designing a Real-Time Control System for an Autonomous Vehicle

    Context

    An automotive company is developing a software system to control an autonomous vehicle.

    Key Concepts
    • Cohesion
    • Coupling
    Sections
    1. Introduction:

      • Describe the purpose of the autonomous vehicle control system.
      • Explain the safety and reliability requirements.
    2. System Architecture:

      • Describe the architecture of the control system, including the key components (e.g., perception, localization, planning, control).
      • Explain how the system processes data from various sensors (e.g., lidar, radar, cameras).
    3. Module Design:

      • Analyze the modules in the system and their responsibilities.
      • Evaluate the cohesion within each module.
      • Evaluate the coupling between modules.
    4. Real-Time Performance:

      • Discuss how the system is designed to meet real-time performance requirements.
      • Explain the use of real-time operating systems and scheduling algorithms.
    5. Safety and Reliability:

      • Describe the design principles and techniques used to ensure the safety and reliability of the system.
      • Explain how the system handles faults and failures.
    6. Testing:

      • Describe the testing strategy, including unit tests, integration tests, and system tests.
      • Explain how the system is tested in simulation and on real vehicles.
    7. Deployment:

      • Discuss the deployment process, including how the software is deployed to the vehicle’s control units.
      • Explain how software updates are managed.
    8. Metrics:

      • Define real-time performance metrics (e.g., latency, jitter).
      • Define safety and reliability metrics (e.g., failure rate, mean time between failures).
    9. Conclusion:

      • Summarize how cohesion and coupling influenced the design of the system.
      • Discuss the challenges and best practices for developing autonomous vehicle control systems.
    Expansion
    • Analyze the use of specific software frameworks and standards (e.g., ROS).
    • Discuss the ethical and legal considerations related to autonomous vehicles.

    Case Study 10: Developing a Large-Scale E-learning Platform

    Title

    Cost Estimation and Scalability Analysis for a Large-Scale E-learning Platform

    Context

    A company is developing an e-learning platform with a wide range of courses and a large number of users.

    Key Concepts
    • COCOMO Model
    • Project and Process Metrics
    Sections
    1. Introduction:

      • Describe the purpose and features of the e-learning platform.
      • Explain the target audience and the expected number of users.
    2. Feasibility Analysis:

      • Discuss the technical, economic, operational, and schedule feasibility of the e-learning platform development.
    3. COCOMO Model Application:

      • Estimate the size of the e-learning platform.
      • Apply the COCOMO model to estimate the effort, cost, and schedule.
      • Discuss the factors that affect the cost of developing a large-scale e-learning platform.
    4. Scalability Analysis:

      • Analyze the scalability requirements of the platform.
      • Discuss the architectural design and technologies used to ensure scalability.
    5. Project Planning:

      • Outline the project plan, including phases, activities, and milestones.
      • Define the project deliverables and acceptance criteria.
    6. Metrics:

      • Define project metrics (e.g., time to market, budget adherence).
      • Define process metrics (e.g., content creation rate, user registration rate, system response time).
    7. Technology Stack:

      • Describe the technologies used to develop the platform (e.g., programming languages, databases, learning management systems).
      • Explain how these technologies support scalability and performance.
    8. Testing:

      • Describe the testing strategy, including unit tests, integration tests, system tests, and user acceptance testing.
      • Explain how the platform is tested for functionality, performance, and scalability.
    9. Conclusion:

      • Summarize the cost estimation and scalability analysis.
      • Discuss the challenges and best practices for developing large-scale e-learning platforms.
    Expansion
    • Compare different learning management systems (LMS).
    • Discuss the use of cloud computing for e-learning platforms.

    IITB Virtual Lab Nodal Centre

    Virtual Labs project is an initiative of Ministry of Education (MoE), Government of India under the aegis of National Mission on Education through Information and Communication Technology (NMEICT). This project is a consortium activity of twelve participating institutes and IIT Delhi is coordinating institute. It is a paradigm shift in ICT-based education. For the first time, such an initiative has been taken-up in remote‐experimentation. Under Virtual Labs project, over 175 Virtual Labs consisting of approximately 1590+ web-enabled experiments were designed for remote-operation and viewing. Technocrats Institute of Technology, Bhopal is conducting workshops and lab sessions under this environment as Virtual Labs Nodal Centre.

    Cloud Computing Course Module

    • Cloud Concepts
    • Basic concepts of cloud computing
    • AWS Cloud value proposition (cost, agility, elasticity, etc.)
    • Principles of cloud economics (CapEx vs. OpEx, pay-as-you-go model)
    • Different types of cloud models (IaaS, PaaS, SaaS)
    • Core AWS services: EC2, S3, RDS, Lambda, VPC, CloudFront, etc.
    • How to deploy using the AWS Management Console and CLI
    • Understanding networking basics (VPC, Subnets, Security Groups)
    • AWS support plans and their features.
    • AWS global infrastructure (Regions, Availability Zones, Edge Locations)

    Faculty: Prof. Hemant Vyas

    Capgemini’s “CodeXperience Lab”

    Capgemini and the Technocrats Institute of Technology (TIT) in Bhopal have a significant partnership, including Capgemini’s “CodeXperience Lab” at the institute and numerous placement opportunities for TIT students. The CodeXperience Lab aims to bridge the skills gap and provide hands-on learning for future tech leaders.

    Key Aspects of the Partnership:

    • CodeXperience Lab:

    Capgemini has established the first CodeXperience Lab in India at TIT, providing students with practical, industry-relevant training.

    • Training Programs:

    Capgemini conducts training programs for selected students, focusing on preparing them for the challenges of the tech industry and fostering innovation.

    Partnership Focus:

    The partnership aims to enhance student skills, bridge the skills gap, and provide opportunities for students to learn and grow within the Capgemini ecosystem.

    KPIT Mobility Innovation Studio

    The KPIT Mobility Innovation Studio was recently inaugurated at Technocrats Institute of Technology (TIT) Bhopal. This collaborative initiative between KPIT and TIT aims to enhance student engagement with mobility technology, focusing on connected, autonomous, and electric mobility. The studio will provide a platform for students to experiment and gain hands-on experience in these areas.

    Key aspects of the KPIT Mobility Innovation Studio at TIT:

    Focus on Mobility Technologies:

    The studio is dedicated to connected, autonomous, and electric mobility, aligning with industry trends and future advancements.

    Hands-on Learning:

    It provides students with practical experience and opportunities to experiment with cutting-edge technologies.

    Industry Collaboration:

    • The collaboration between KPIT and TIT bridges the gap between academic learning and industry expectations.
    • Nurturing Innovation:

    The studio aims to foster innovation and creativity among students in the field of mobility.

    DSPL TECHNOLOGIES: JOURNEY, TEAM, PROJECTS & COMMUNITY IMPACT (2021–2025)

    Introduction

    DSPL Technologies, founded in 2021, is a pioneering organization driven by innovation and a commitment to transforming education, technology, and entrepreneurship for students across India. With a strong vision to empower young minds, DSPL has grown into a vibrant community of developers, designers, strategists, and learners working collaboratively to bring real-world solutions to life.

    Founder’s Vision

    Founder & CEO: Mr. Udit Jain
    A visionary technologist and entrepreneur, Mr. Udit Jain laid the foundation of DSPL Technologies with the mission to bridge the gap between academic learning and industry requirements. Under his leadership, the organization has grown from a small student initiative into a nationwide movement empowering thousands of students.

    Core Leadership Team

    Managing Director (MD): Shubham Ghodeshwar
    Chief Financial Officer (CFO): Aashi Tiwari
    Chief Marketing Officer (CMO): Priya Sarode

    Team Members

    DSPL Technologies boasts a diverse and dynamic team spread across various regions of India, contributing to different domains of project development and training.

    • Nimisha Sahu
    • Tanupriya Jain
    • Shardha Sahu
    • Yash Tiwari
    • Ramya Shree
    • Rajiv Baghel
    • Vaishnavi Shinde
    • Vaishnavi Rajhans

    Note: In addition to the core team, DSPL has active contributors and regional leaders from various states of India who support the development and outreach efforts of the organization.

    Achievements and Milestones

    Projects Delivered
    DSPL Technologies has successfully developed and launched 40+ innovative projects in the market across domains such as:

    • Cybersecurity
    • Web & App Development
    • AI/ML-based solutions
    • Education tech tools
    • SaaS platforms

    Ongoing & Upcoming Projects

    Currently, DSPL is actively working on over 100 new development projects, aimed at solving real-world problems and providing scalable digital solutions.

    Training & Internship Programs

    In 2023 alone, DSPL provided hands-on training and internship opportunities to 5000+ students.
    Many of these interns are now successfully placed in reputed companies, having gained real-time exposure and skills through DSPL’s structured programs.

    DSPL Community & Ecosystem

    DSPL Technologies is not just a company; it is a community-driven movement. Here’s what sets the DSPL community apart:

    • DSPL Learn: A training initiative providing free and paid courses in development, AI, cybersecurity, and soft skills.
    • DSPL Launchpad: A startup accelerator helping students and early-stage founders turn their ideas into scalable ventures.
    • DSPL Talent Hub: A dedicated platform for students to showcase their portfolios and get hired based on real skills.
    • Webinars, Hackathons & Events: Regular national-level hackathons, coding competitions, mentorship sessions, and workshops.
    • Student Chapters: Active DSPL student chapters in colleges across India, promoting leadership, innovation, and project-based learning.

    DSPL Journey: 2022–2025

    2022: The Beginning

    • DSPL was founded with a vision to empower college students through real-world tech exposure.
    • Initial team formation and prototype projects.

    2023: Expansion & Recognition

    • Official incorporation of DSPL Technologies.
    • Launch of internship programs impacting 5000+ students.
    • Collaboration with institutions and industry experts.
    • Expansion of team and state-level outreach.

    2024: Innovation at Scale

    • Successful deployment of 40+ projects.
    • Establishment of DSPL Learn and DSPL Launchpad.
    • Community crosses 15,000 members pan India.
    • Training programs expanded to rural colleges and Tier-2/3 cities.

    2025: Towards a Tech-Driven Future

    • Focus on building 100+ scalable development projects.
    • Launch of the DSPL Startup Platform for investor and mentor connect.
    • Vision to become one of India’s top student-driven tech communities.
    • Strengthening global collaboration and placement pipelines.

    DSPL Technologies: Projects, KT Sessions & Achievements (2021–2025)

    1. Timeline of Key Projects (2021–2025)

    2021 (Pre-Launch Phase – Idea to Initiative)

    • Conceptualization of DSPL Technologies by a group of passionate engineering students.
    • Initial projects were self-funded prototypes focused on:
      • Campus Security Systems
      • Student Attendance Automation using QR
      • Online Examination System

    2022 (Foundation Year – Official Launch)

    • DSPL Technologies officially founded and launched.
    • Key Projects:
      • CyberWall
      • DSPL Vault
      • DSPL TaskHub
    • First KT Session conducted at [Your College Name] titled “CyberSafe Campus”, attended by 300+ students.

    2023 (Expansion & Market Entry)

    • Projects Deployed:
      • MedEasy
      • EcoTrack
      • SmartFeedback
      • DSPL Careers Portal
    • KT Sessions in 20+ engineering colleges across multiple states.
    • Partnered with startups for internships.
    • Reached 5000+ students.

    2024 (Innovation & Leadership)

    • Flagship Projects:
      • ShadowOS
      • SkillNet
      • DSPL CampusApp
    • KT Sessions in 30+ colleges with hands-on activities.
    • DSPL Community crosses 15,000+ members.
    • Students placed in top companies.

    2025 (Future-Driven Development & Scale-Up Year)

    • Currently developing 100+ new projects:
      • AI-Powered Education
      • FinTech Apps for Students
      • Healthcare Monitoring Devices (IoT-based)
      • Secure Payment Gateways
    • DSPL Startup Platform launch.
    • National KT plans and target to train 10,000+ students.

    2. Major Achievements of DSPL Technologies (2021–2025)

    • 40+ fully functional projects deployed in real-world environments
    • 5000+ students trained/interned by 2023
    • 100+ colleges reached through KT sessions, events, workshops
    • Active DSPL community with 15,000+ members across India
    • Multiple project wins in inter-college/state hackathons
    • Featured in regional startup summits and college innovation expos
    • Empowered Tier-2 & Tier-3 college students with practical tech exposure
    • Actively promoting women in tech leadership with 50% female team leaders
    • Created direct placement pipelines for trained students via DSPL TalentHub
    • Enabled multi-language tech education: Sessions conducted in Hinglish, Marathi, Hindi, Telugu

  • “A Case study on Economical Improvement of Power Factor by Reactive Power Compensation”

    Abstract: Nowadays the demand for power sector is increasing. Everyone needs uninterrupted, reliable power supply. The cost of generating electrical energy is increasing due to non-availability of raw materials like coal, fuel, water etc. Major energy sources like coal and fuel are facing huge depletion as they are non-renewable. In such cases there is regular loss of energy in industries like transmission and end users.

    Industries are working with inductive loads like transformers, motors, inductive furnaces etc. where most of the energy is being wasted due to low ‘power factor’. The most important task is to prevent energy from being wasted.

    Waste energy efficiency, also known as poor power factor, is often overlooked. This can result in poor reliability, safety problems, and high energy costs. The lower the power factor, the weaker the economic system. The actual amount of power dissipated in the circuit as a function of resistance is called real power (KW).

    Reactive loads like inductive, capacitive make up power are called reactive power (KVAR). The linear combination of real power and reactive power is apparent power (KVA). The power system becomes unstable because a factor called reactive power causes low power factor.

    Power factor improvement is usually achieved by adding a capacitive load to offset the inductive load present in the power system. The power factor of a power system is constantly changing due to the size and number of motors used at one time. This makes it difficult to balance such loads.

    Power factor correction has many benefits like reduction in peak demand, energy saving, reduction in utility billing, avoiding wastage of power, adds life to electrical appliances.

    Present power condition analysis at plant: Govindpura, Bhopal 220/11 KV Substation for load operation. Demand for contract with 12MVA Amrit Wires and Cables. Power supply boards prefer 0.9 power factor. When our plant is in full operation i.e. GM and thermal section, the power factor is around 0.92. According to government organization this is good, but not economically good for high industrial loads and even consumption much more than what we are actually using.

    Only HV distribution is discussed here. The 0.88 MTPA pellet plant has 10 operational High Tension (HT) motors and the total HT motor load is 7510 kW. This high inductive load is generating unwanted reactive power (Q). Table 1 below is showing the motor load current and its average power factor.

    HT motors load current at its average working PF

    Motor KW PF Current Load Current Load PF Quantity
    Grinding Mill Motor 1800 0.83 115 83 0.87 1
    GM ID fan Motor 1800 0.82 115 79.5 0.86 1
    ESP ID Fan Motor 1250 81 37 0.78 1
    Travelling Grate Motor 450 29.1 16 0.82 2
    Cooling Motor 250 17.2 14 0.67 3
    Cable Grinding Mill Motor 450 0.81 29.3 13 0.54 1
    CG ID Fan Motor 560 36.2 23 0.78 1

    Each HT motor is generating reactive power, but the magnitude of reactive power is higher than that of GM main motor and ID fan motor because their power capacity is 1800kW in total. Table shows that the vertical grinding mill motor is operating at 0.86 pF (average value) and the ID fan motor is operating at 0.88 pF (average value). There is no need for this bad power factor. Here are some analyzes as shown below,

    Major section like GM, Thermal and CGM are important parts of plant.

    If these 3 sections run simultaneously, power factor will be =0.91

    If GM and thermal in operation, power factor will be = 0.92

    If CGM and thermal in operation, power factor will be = 0.94

    If GM in operation, power factor will be = 0.95

    If thermal only in operation, power factor will be = 0.98

    As mentioned above the power factor is decreasing when the plant is in full operation. But this is good only when the thermal section of the plant is operational. With these practical results, we can say that the power factor is mainly decreasing due to HT motors in the GM field. Some analysis has been done for both motors.

    Grinding Mill Motor:

    Case -1

    Name plate of HT motor, 1800KW, 11KV, 118.6A, 922RPM, 0.84 pf

    We know that, Power factor = Cosø = (KW) / (KVA)

    Readings taken during the operation of motor, KVA and KVAR is calculated and shown in the table below. (SCADA System)

    Motor working pf, reactive power at 65 to 85 % of its capacity

    Power in KW Current in A P.F (Cosø) KVA Volt–Amp Sinø KVAR Volt-Amp-Reactive
    1199 88 0.89 1347 0.455 612
    1056 84 0.81 1303 0.585 762
    1285 82 0.85 1511 0.526 794
    1364 74 0.88 1550 0.474 734
    1343 92 0.88 1526 0.474 723
    1338 100 0.88 1520 0.474 720
    1100 95 0.86 1279 0.51 652
    1310 89 0.87 1505 0.493 741
    1283 69 0.85 1509 0.526 793
    1327 63 0.87 1525 0.493 751
    1197 78 0.84 1425 0.542 772
    1386 85 0.89 1557 0.455 708
    1262 92 0.87 1450 0.493 714

    After doing the analysis of above table 2, results are as follow:

    Motor is running at 70 to 80 % of full load capacity

    KVAR is being generating from motor, even though there is 900KVAR capacitor bank in the HT room.

    Some power losses because of low pf

    Average value of power KW is = 1265 KW

    Average value of current IL is = 83.9 A

    Average value of Pf = 0.86

    Average value of KVA demand = 1462

    Average value of KVAR is = 728.9

    GM – ID Fan Motor:

    Case – 2

    Name plate details of HT motor, 1800KW, 11KV, 115A, 0.86pf, 1494RPM

    We know that, power factor = Cosø = (KW) / (KVA)

    Readings noted down during the operation of motor, KVA and KVAR is calculated and shown in the table 3. (SCADA System)

    Table 3: Motor working pf, reactive power at 70 to 80 of its capacity

    Power in KW Current in A P.F (Cosø) KVA Volt–Amp Sinø KVAR Volt-Amp-Reactive
    887 80 0.9 985.5 0.435 428.6
    906 80 0.9 1006.6 0.435 437.8
    809 80 0.87 929.8 0.493 458.3
    924 78 0.89 1038.2 0.455 472.3
    839 79 0.88 953.4 0.474 451.9
    808 80 0.87 928.7 0.493 457.8
    917 79 0.9 1018.8 0.435 443.1
    835 80 0.88 948.8 0.474 449.7
    837 80 0.88 951.1 0.474 450.8
    935 80 0.9 1038.8 0.435 451.8

    After doing the analysis of above table 3, results are as follow:

    Motor is running at 70 to 80 % full load capacity

    KVAR is being generating from motor, even though there is 900KVAR capacitor bank in the HT room.

    Some amount of power losses because of low pf

    Average value of power KW is = 869.9

    Average value of current IL is = 79.6

    Average value of pf = 0.88

    Average value of KVA demand is = 979.9

    Average value of KVAR is = 450.2

    Important points to consider:

    Hence 520KVAR capacitor bank is sufficient for economical power factor for the mill motor.

    ID fan motor requires 450 KVAR capacitor bank depending on the current load condition

    The total percentage of loss reduction for motors will be approximately 42.6%. In this way a lot of wastage of electricity will be reduced.

    Industry will get power factor incentive by maintaining power factor 0.98

    Power factor correction does not neutralize more than 82% of the magnetic flux generated.

    Compensation: Sometimes it is possible to correct the power factor of several loads by means of a common capacitor. This involves connecting a fixed or automotive type capacitor to a group of inductive loads operating simultaneously.

    The average power consumption of the plant is 5000 KW at 0.92 power factor and 2000 KVAR with all inductive loads being generated continuously.

    The following table will give the details like KVA demand, power factor

    Months Contract Demand (KVA) Recorded Demand (KVA) Recorded PF
    Feb 12000 6664 0.92
    March 12000 6349 0.93
    April 12000 6202 0.93
    May 12000 6020 0.94

    Power KW = KVA (Contract Demand) x PF
    = 12000 x 0.92
    = 11040

    KVAR required = KW x (Tan (cos-10.92) – Tan (cos-10.98))
    = 11040 x (Tan 21.5 – Tan 11.47)
    = 11040 x (0.3939 – 0.2029)
    = 11040 x 0.191
    = 2108

    Hence to improve the power factor from 0.92 to .98, “2200 KVAR Capacitor Bank” is required. Power factor correction does not neutralize more than 80% of the magnetic flux generated.

    References:

    Conclusion:

    PFC helps the organization to save energy in terms of electricity payment costs. Due to this the power distribution network becomes balanced. Implementation of additional capacitor banks in the power distribution network will stabilize the system.

    Research activities in association with students

    Research Activity 1
    Name of Faculty: Dr Malay Dash
    No of Students Involved: 5
    Design and Simulation of Solar-Biomass Hybrid System for Electrification of Rural Areas.

    The Indian population are increasing day by day and energy demand are also increasing exponentially but the conventional energy sources are limited and exhaustible, not eco-friendly. Solar-biomass based energy system have been deemed clean, inexhaustible, unlimited and environmentally friendly, but solar energy source is dependent on unpredictable factors such as weather and climatic conditions therefore biomass system also used with storage system like battery backup used for continuous energy supply through whole year. The cost of energy generation by solar-biomass system is minimum and system eco-friendly. The main objective of this work is to provide the electric power in remote areas where transmission line are not installed or power available only for few hours therefore on the basis of survey conducted in village Sihada (MP) for electricity requirement, a stand-alone solar-biomass hybrid system is proposed. The main drawback of traditional solar panel is its low efficiency up to 30% therefore biomass system is used.

    HOMER software is used for simulation & optimization of the solar-biomass hybrid system. This software use the input data provided by user and take different combinations of feasible system for a particular place.

    In our work we concentrate on only solar-biomass hybrid system. This assignment will study the suitable biomass hybrid models with solar Thermal in order to explore the possibility of optimizing fuel usage and making plants more sustainable. Biomass hybrid model may provide the solution to overcome these barriers as two renewable energy resources complementing each other with regard to availability.

    The use of fossil fuels and nuclear energy replaced totally the non-conventional methods because of inherent advantages of transportation and certainty of availability; however, these have polluted the atmosphere to a great extent. In fact, it is feared that nuclear energy may prove to be quite hazardous in case it is not properly controlled.

    The limited reserves of fuel oils and their unstable prices have significantly increased the interest in renewable energy sources. The design of hybrid solar-biomass power systems (HSBPS) has received considerable attention in the last decade.

    Now day’s applications with photovoltaic (PV) energy and biomass energy have been increased significantly due to the rapid growth of power electronics techniques. Generally, PV power and biomass power are complementary since sunny days are usually calm and low PV power is often occurred at cloudy days or at night time. Hence, the PV/Biomass hybrid power system therefore has higher reliability to deliver continuous power than either individual source. Traditionally, a substantial energy storage battery bank is used to deliver the reliable power and to draw the maximum power from the PV arrays or the biomass generator for either one of them has an intermittent nature. However the battery is not an environmental friendly product because of its heavy weights, bulky size, high cost, limited life cycles, and chemical pollution. Therefore, solar – biomass hybrid system is more economical as compared to stand alone system.

    OBJECTIVES
    The objective of this work is:Cost analysis of solar-biomass hybrid system for remote areas where electricity transmission line not presents or if present than power supply only for few hours in a day. This biomass hybrid system with solar thermal in order to explore the possibility of optimizing fuel usage and making plans more sustainable.

    Solar-Biomass based hybrid system may provide the solution to overcome these barriers as to renewable energy resources complementing each other with regard to availability. Number of villages in India is still waiting for electrification and villagers want to fulfill for their daily needs like cooling and lighting.

    CONCLUSION
    In India number of villages is un-electrified and some village which are electrified but suffering the power supply or power failure problem due to lack of power generation or transmission line installation problem. In the situation the Solar-Biomass based Hybrid is the best option for electrification of villages which are suffering power problem since independence of India.

    The Solar power is available free of cost and Biomass product like wood chips, saw dust, rise husk and wheat husk etc. available in village area in lot of amounts. Solar power converted into electric power by solar panel which is eco-friendly and biomass energy converts into electric power by gasifier system which is also eco-friendly system. On the basis of economical point of view Solar-Biomass Hybrid system is also best system the cost of energy is 4.27 rupees per unit in installation year and from next year the cost of energy is reduced from 4.27 rupees per unit.

    Based on Research Work Project was designed
    The suggestions/ Review / feedback can be sent on Malaya_rec2rediffmail.com

    Research Activity 2

    Name of Faculty: Dr. Saurabh Gupta
    No of Students Involved:6
    SOLAR ENERGY BASED ELECTRIC VEHICLE CHARGING STATION
    A green energy based Electric Vehicle Charging Station (EVCS) is proposed which provides electricity to EV as well as Battery Storage System(BSS). Among all renewable energy sources, the solar PV system is best option because of abundance and easy to operation. However, solar PV power fluctuates due to change in irradiance and temperature and it cannot generate the constant power, therefore to compensate the power fluctuation a standby battery storage system is needed to meet up the power demand and maintain the reliability of the EVCS. Thereby, a DC micro grid system has been developed which consist of BSS along with the solar PV system and electric vehicle (EV) battery charger. The power generated from solar PV system is not sufficient to fulfill the demand during this time BSS supports to charge the EV. On the other hand, while generation is more than demand than BSS charge sufficiently. This results in a robust, without grid support, pollution-free and efficient green EV charging station. Furthermore, this proposed system has been implemented in environment of MATLAB/Simulink so that we can verify the performance of system. This thesis contains a hybrid dc micro grid to reduce the processes of conversions of multiple dc–ac–dc or ac–dc–ac. The hybrid grid consists of only dc networks that are connected together by two bidirectional converters one at the electric vehicle side and other is at the battery storage system side. Battery storage systems (BSS) can be connected to dc or ac links. The proposed hybrid grid can operate in a autonomous mode that is off-grid mode. The control algorithms are here proposed for getting constant voltage at DC bus between these dc links and also for operation of stable system under various generation and load conditions. Uncertainty and intermittent characteristics of solar irradiation level, ambient temperature, wind speed, and loads are also considered in system operation and control. A small hybrid dc grid has been simulated and modeled using the Simulink tool in the MATLAB. The MATLAB/simulation results show that this proposed system can maintain the stable operation under the proposed control schemes explained in this work.

    RESEARCH METHOD

    The objective of this research is to charge an electric vehicle using green energy sources and also to make the voltage constant at DC micro grid. The objectives are given in steps below:

    • To charge the electric vehicles from the renewable energy sources by using constant voltage approach with a dc micro grid.
    • To minimize the voltage fluctuations of dc micro grid with the help of proposed voltage

    CONCLUSION
    The main objective of EV transportation is noise free and pollution free environment. Using the solar powered charging station will result in an enormous decrease in pollution level of environment but some barriers of solar powered CS restrict us to use this for a large level of deployment. Hence, using the MPPT technique here to extract the maximum power from the solar cells. There is also a point to focus on and that is the fluctuation in DC grid voltage. This helps to propose a green energy based electric vehicle CS and also ensure the constant DC bus voltage with the help of fuzzy based PI controller which will also improve the battery life span. To improve the waveform of DC grid voltage, we will replace the conventional controller (PI controller) with a controller that will result in less fluctuation in voltage and also is simple to install in any system and fuzzy logic controller will satisfy all our fulfillments. Fuzzy based PI controller is better than conventional PI controller it is also verified with the help of MATLAB results in our proposed work. Furthermore, this work will extend to for a hybrid renewable energy sources and energy storage system.

    Based on Research Work Project was designed

    The suggestions/ Review / feedback can be sent on saurabhgupta.sgsits@gmail.com

    Research Ideas by 1st Students

    Sr No Student Name Mobile No Topic Remark
    Group – 1
    1 ADARSH KUMAR 7209105990 To increase efficiency of EVs and cost Improving the efficiency of electric vehicles (EVs) is key to extending their range, reducing energy consumption, and enhancing overall performance.
    2 ALOK ADHIKARY 8699155402
    3 AMAN KUMAR 9608401373
    4 ANKUSH AHIRWAL 8641088728
    Group – 2
    5 ANURAG GAROTHIYA 9589111472 Concept of Hyperloop Hyperloop is an ultra-high-speed ground transportation system for passenger and cargo
    6 ANURAG TIWARI 9341353859
    7 BILKAISH IMAM 8709274937
    8 DEEPENDRA SHARMA 7869151578
    Group – 3
    9 DHAMENDRA AHIRWAL 9399074915 Exercise Electric Device Use our waste energy during any type of exercise to create or convert into electrical energy by using that electrical device. That would be simple
    10 HIMANSHU KUMAR 7061147895
    11 KRRISH KUMAR 9341426537
    12 KUNAL SINGH 7050601094
    Group – 4
    13 MD IRSHAD KHAN 9304390734 Design a sensor to be put in helmet of person driving EV Bike Prevents accidents and alarms when speed limit is exceeded.
    14 MOHIT JAITWAR 7067097490
    15 PRIYANSHU KUMAR 8709262589
    16 PIYUSH PASWAN 7771003969
    Group – 5
    17 NITYAM KUMAR VERMA 7488396647 A helmet with sensor which warns about nearby vehicles for safety reasons Helmet alerts about nearby vehicles
    18 RITESH SHILPKAR 8225867188
    19 SAURABH KUMAR 6205410560
    20 SHISHU KUMAR 7033566856
    Group – 6
    21 SOURABH KUMAR 9039723918 Magnetic Properties in Cars by using that property to avoid accidents
    22 SUDHANSHU KUMAR 9798673496
    23 SURAJ KUMAR 7562027967
    24 TAMRAJDHWAJ LONI 9301290561
    Group – 7
    25 VANSHIKA SHRIVASTAVA 6266483102 Building Integrated Photovoltaic (BIPV) systems refer to solar power generating systems that are integrated into buildings
    26 VIKAS KUMAR 7061626186
    27 VINAY KUMAR 6201209216
    28 ZISHAN ALAM 8271221369
    29 JOGENDRA AHIRWA 8103516627

    Learning support for students and faculty

    Learning Support for Students and Faculty Members
    • Expert Lectures, Seminar and Workshops
    • Training on PLC & SCADA
    • Workshop on Entrepreneurship
    • Workshop on Design and Development of Drones
    • Quiz Competitions
    Use of Modern Tools and Techniques
    • Training on software like MATLAB etc.
    • Hands-on Practice Session on PLC
    • Group Discussion
    • Paper Presentation Competitions

    Seminar on Drone Technology

    Department: Department of Electrical & Electronics Engineering

    Semester: B. Tech III, V & VII Students

    Activity: Seminar

    Date: 26.04.2022

    Title: Seminar on Drone Technology.

    Resource person/agency and affiliation: Mr. Yashraj Sunhare, Co-founder & CEO – Jarvis Labs Pvt. Ltd. Bhopal

    Convener: Dr. Saurabh Gupta

    Executive Summary: Seminar on “Drone Technology” was organized successfully, at TIT & S, Bhopal by the Department of Electrical & Electronics Engineering, TIT & S, Bhopal on date 26.04.2022.

    The workshop aimed to provide students with comprehensive knowledge in designing of drones. The expert for the training was Mr. Yashraj Sunhare, Co-founder & CEO – Jarvis Labs Pvt. Ltd. Bhopal

    Seminar Objectives:

    The primary objectives of the seminar were to:

    1. Make students about development of utility-based drone that provide assistance agriculture, surveillance, heavy payload lift, disaster relief management, surveying & inspection. Introduction to Drones and Basic principles of flight.
    2. Provide knowledge to students about designing of a Drone from scratch. Dimensioning, Motor, ESC and Propeller selection Hands-on with Motors, ESCs, Propellers, FCB, Transmitter-Receiver, Battery and Frame.
    3. Make students to aware about the recent employment possibilities in drone technologies.
    Outcomes and Feedback
    • Students learned the basic knowledge about drone technology and the future of the drone industry with great enthusiasm and presented their points efficiently.
    • Students learned the basic principles of flight.
    • Students acquired knowledge about autonomous drones and mission planning.
    • Students became aware of the applications and use of drones in India, government initiatives, and DGCA regulations (Civil Aviation Requirements).
    Conclusion

    Seminar on “Designing of Drones” organized successfully, at TIT , Bhopal will provide knowledge about development of utility-based drone that provide assistance agriculture, surveillance, heavy payload lift, disaster relief management, surveying & inspection. Students learned the basic knowledge about drone technology and future in drone industry with great enthusiasm and kept their points efficiently.

    No. of participants: 60

  • Title: Mobile and Cell radiation

    Method: Case study has been carried out to assess radiation intensity of cell towers. Research articles on radiation effect discussed and survey was done by the students during industrial visit at cell sites of mobile service providers.

    Outcome: Students were able to understand that high radiation affects human health.

    Action Taken: Safety measures are discussed with students while exposing to radiation.

     

    Students:

    Faculty Mentor: Prof. Sandip Nemade, Prof. Neeraj Tiwari

    Name of faculty: Dr. Arvind Sahu

    Students Involved in Collaborative research with faculty

    S No Name Enrolment No
    1 Ankit Anand 0111EC181017
    2 Mayank Yadav 0111EC181063
    3 Prakrati Shukla 0111EC181078
    4 Prity Singh 0111EC181082
    5 Tejasvi Singh 01111EC181115

    Medical Assistance Robots

    Abstract

    RoboCare-Med is an advanced medical assistance robot designed to revolutionize patient care and healthcare The healthcare landscape is continuously evolving, with an increasing demand for advanced technologies to enhance patient care, improve outcomes, and optimize healthcare delivery. One area where significant advancements have been made is in the development of medical assistance robots. These robots play a crucial role in addressing various challenges faced by healthcare professionals and institutions:

    Need for Medical Assistance Robots

    Aging Population: With the global population aging rapidly, there is a growing demand for healthcare services, particularly in areas such as elderly care and chronic disease management. Medical robots can assist in tasks like patient monitoring, medication management, and mobility support, thereby alleviating the strain on healthcare providers and improving the quality of care for elderly patients.

    Precision and Accuracy: Medical procedures often require a high degree of precision and accuracy. Robots equipped with advanced sensors, imaging technologies, and robotic arms can perform tasks with greater precision than human hands, reducing the risk of errors and improving surgical outcomes.

    Minimally Invasive Procedures: The trend towards minimally invasive surgeries has led to the development of robotic systems that can perform complex procedures through small incisions. These robots offer surgeons enhanced dexterity and control, leading to faster recovery times, reduced complications, and improved patient satisfaction.

    Workforce Shortages: Many healthcare systems face challenges related to workforce shortages, especially in specialized areas such as intensive care units (ICUs) and emergency departments. Medical robots can supplement existing healthcare staff by automating routine tasks, allowing human providers to focus on critical patient care activities.

    Remote Healthcare: Telemedicine and remote healthcare services have become increasingly important, especially in rural or underserved areas. Medical robots equipped with telepresence capabilities enable remote consultations, diagnostics.

    Infection Control: Infection control is a paramount concern in healthcare settings, particularly in light of global pandemics such as COVID-19. Robots can be designed for tasks that minimize direct human contact, such as disinfection, sterilization, and delivery of supplies, contributing to a safer healthcare environment.

    Data-driven Decision Making: Medical robots integrated with artificial intelligence (AI) and data analytics can analyze vast amounts of patient data in real time, providing valuable insights for clinical decision-making, personalized treatment plans, and predictive analytics for disease management.

    In conclusion, the need for medical assistance robots arises from a combination of demographic shifts, technological advancements, healthcare challenges, and the pursuit of improved patient outcomes. These robots represent a transformative force in modern healthcare, offering innovative solutions to complex healthcare problems and shaping the future of medical practice

    Conceptual Design and Prototyping:

    1. The conceptual design phase involves creating initial design concepts, sketches, and mock-ups of the RoboCare-Med robot. Multiple design iterations may be explored to evaluate different concepts and refine the design based on feedback from stakeholders.
    2. Computer-aided design (CAD) software is used to create detailed 3D models of the robot, including its physical structure, components, sensors, actuators, and user interfaces. Virtual simulations and prototypes are developed to assess the feasibility and functionality of the design.

    Training Activity for students

    • Training on software’s – Python , C, C++, Java
    • Hands-on Practice session on IoT, MATLAB, Microcontroller & Embedded system, VLSI Design
    • Training on Aptitude and reasoning
    • Internal SIH
    • Expert Lectures and workshops

    Training Activity for Faculties

    • Faculty development program
    • Workshops
    • Short term training program
    • Expert Lectures
    • Software training

    Student Support:

    Tutoring Services: Offer peer tutoring or faculty-led tutoring sessions to help students with difficult concepts or coursework.

    Workshops and Seminars: Organize workshops and seminars on topics like programming languages, circuit design, communication protocols, and industry trends.

    Online Resources: Provide access to online learning platforms, educational videos, and interactive simulations for self-paced learning.

    • E library : In this e- learning facility some e- books are provided for the students bar code is provided here

    Lab Facilities: Ensure well-equipped labs with modern equipment for hands-on learning and experimentation.

    Study Groups: Encourage students to form study groups to collaborate on projects, discuss coursework, and support each other.

    Central Library: In this students can refer several books, Journals, News papers

    Faculty Support:

    Professional Development: Arrange workshops, conferences, and training programs to enhance faculty skills in teaching, research, and industry engagement.

    Curriculum Enhancement: Collaborate with industry experts to update the curriculum with the latest technologies, case studies, and real-world applications.

    Research Funding: Facilitate grants and funding opportunities for faculty research projects in areas like IoT, signal processing, telecommunications, etc.

    Mentoring Programs: Establish mentoring programs where experienced faculty members guide junior faculty in teaching methodologies, research strategies, and professional growth.

    Teaching Resources: Provide teaching resources such as lesson plans, assessment tools, and teaching aids to support effective classroom instruction.

    By implementing these support measures, we can create a conducive learning environment for both students and faculty in the electronics and communication branch.

  • Title: Traffic Volume Survey

    Name of the students: Ayush Garg, Rahul Pandey, Piyush Kumar

    Faculty Mentor: Ms. Mayuri Patel

    Department has offered case study to assess the width of flexible pavement between Piplani Petrol pump to Bhopal-Indore Bypass Road. Traffic survey was conducted by the students. Based on Traffic Volume survey during peak hours it was suggested that width of pavement is sufficient to cater the traffic provided the encroachment of road is taken care by adequate number of traffic police personnel at Anand Nagar.

    Action taken: The Recommendations were forwarded to commissioner of National Highway authority for benefit of residents and road-users. The outcome was removal of encroachment and now there is no traffic jam conditions.

    Title: Ground Water Quality Analysis in Govindpura Area

    Name of the students: Sarman Kushwah, Aman Patel, Shashank Dangi , Gajanand

    Faculty Mentor: Mr Harish Nema

    Ground water is the major alternative source of water of Bhopal city. About twenty ground water samples were collected from Govindpura Industrial area. Study of some physico -chemical parameters of ground water was carried out using Indian Standard Code IS 10500. Acidity, Alkalinity, Chlorides obtained are within permissible limits but Turbidity, total hardness and iron content of some samples are beyond the permissible limit of drinking water standards. From the Bacteriological analysis it can be concluded that water is contaminated.

    The industrial activities, dense vehicle movement and industrial waste water discharge and its intermixing in ground water may be the probable reason for the same.

    Action taken: The Recommendations were forwarded to M.P. Pollution Control Board.

    Research activity 1

    Name of Faculty: Dr Kashfina Kapadia Memon (HOD)

    No of students involved in the activity: Four

    Abstract:
    Water is the need of the society. It should reach to each and every consumer in sufficient quantity, potable in quality and at suitable pressure. The design of water distribution network is an optimization problem where cost is to be minimized by using pipes from a list of discrete commercially available pipe sizes. By using different methods like Linear programming, Non-linear programming, Gradient method, Newton Raphson Method etc have been used in the past but due to discrete nature of pipe diameters and non-linear constraints the use of evolutionary optimization methods like Genetic Algorithm, Particle Swarm Optimization, Ant Colony Optimization, Differential Evolution, Honey Bee Mating Optimization, Memetic Algorithm, Simulated Annealing, Shuffled Complex Evolution and Harmony Search etc are used for optimization of WDN in recent times.

    Objectives

    1. Developing criteria for design of water distribution system.
    2. Model formulation and development i.e. identification of objective functions and constraints and prepare mathematical model of the selected distribution networks.
    3. Explore the methods of optimization of water distribution network and selection of optimization method based on the literature review.
    4. Identify suitable optimization techniques to propose a robust algorithm to optimize the design of Water Distribution Network. It can be coupled with hydraulic Solver EPANET.
    5. Identify at least two optimization procedures for the design of WDNs for different benchmark problems as well as the real life problems. Identify a real life case study of a large sized WDN to establish its efficacy on the criteria of optimal design.
    6. To produce and present the results of analysis in a systematic manner to draw valid conclusions from the present work.
    7. To draw conclusions from the present study.

    Extension work based on this research work

    • Technical Performance evaluation of water distribution network using EPANET software.
    • Water demand analysis of existing water distribution network of Bhopal City.
    • Water quality modelling of Water Distribution network.
    • Performing Extended Period simulation in Pressure driven demands.

    These projects were given to a group of students as their project. The suggestions are invited from the researchers to explore new dimensions in research.
    The suggestions/ Review / feedback can be sent on kashfina@gmail.com

    Research activity 2

    Name of Faculty: Mr Harish Nema

    Brief Information of Research Work.

    Solid waste management is perhaps the most important service required by urban dwellers to maintain their quality of life. Large amount of solid waste is generated in India, in Urban, municipal and industrial sectors which are finally disposed to the solid waste disposalsites.Bhopal is not an exception. The Bhopal city has 75 acres of land for waste disposal. The waste generated in the city is deposited at this landfill site which is situated in Bhanpura village at a distance of 16 km from the city. No scientific method of waste disposal is adopted. All waste is disposed off at the landfill. This system of disposal by open dumping of waste creates a lot of environmental problems and public health hazards. Madhya Pradesh state Agro Industries Development Corporation limited has set up an Organic manure plant based on solid waste which produces organic manure from the solid waste which is being sold to the farmers of M.P. The organic mantic is made in this plant through Bio-augmentationprocess. The non- biodegradable war left after the segregation from the plant is used for land filling.The landfill site is closed for the dumping of waste since 2018 by Bhopal Municipal Corporation.This Municipal Solid waste is creating a lot of environmental concern in surrounding area. Unscientific disposal of solid waste pollutes the soil as well as ground water sources. The present work aims to find out the ground water and soil pollution post closure impact of dumping site. During the study about twenty four tube wells were selected and samples were collected for Physico-chemical parameters like pH, Turbidity, Electrical conductivity, Total dissolved solids, Chlorides, Total Hardness, Calcium Hardness, Magnesium Hardness, Nitrate and Sulphates.

    Outcome of the work till date
    The results showed higher concentration of contamination in most parameters like conductivity, TDS, chloride, total hardness, calcium hardness, magnesium hardness, which exceeds the limits of standards prescribed by BIS:10500. It was found that ground water near the closed dumping site is contaminated and is not fit for direct drinking purposes. Presence of fecel coliform in the samples indicates disease causing characteristics and may cause intestinal problems to consumers. Improper solid water management has also given rise to problems like health, sanitation and environmental degradation.

    Based on Research Work some Projects were designed. These topics may be given to group of students as their minor/major project.

    1. Environmental Impact Assessment of Solid waste Management – A Case study of Bhapur Area.
    2. Groundwater and Surface water quality analysis of surrounding area of Bhapur village.
    3. The Public’s Perception Regarding Waste Management.
    4. How Recyclable Materials Support Effective Waste Management.
    5. The Impact of Solid Waste on surrounding Environment.

    The suggestions/ Review / feedback can be sent on hnharishnema@gmail.com

    Training Activity for faculty and students

    • Training on software’s like EAG and Benley
    • Hands-on Practice session on Total Station
    • Group Discussion
    • Project Model Competitions
    • Exposure to Conferences on Road Safety
    • Exposure to Interdisciplinary Research

    Learning Support for Students and Faculty Members

    • Expert Lectures and Workshops
    • Training on AutoCAD
    • Online Workshop on Bridge Design
    • Workshop on Stadd Pro
    • Online Quiz Competitions

    Use of Modern Tools and Techniques

    • Training on software like EAG and Benley
    • Hands on Practice session on Total Station.
    • Group Discussion
    • Project Model Competitions

    Hands on Practice session on Total Station

    Department: Department of Civil Engineering

    Semester: B. Tech III & V Students

    Activity: 3 Days Workshop

    Date and Duration: September 05, 2022, to September 07, 2022

    Title: Working and Uses of Total Station on Field.

    Resource person/agency and affiliation: • Er. Amit Gupta, Site Engineer, Smart City Project, Bhopal.

    Convener. Prof SourabhAsange/ Prof Ajid Khan

    Executive Summary The 3-day Workshop on “Working and Uses of Total Station on Field”held at TIT, Bhopal, from September05, 2022, to September 07, 2022, was a resounding success. Organized by the Department of Civil Engineering, the workshop aimed to provide students with comprehensive knowledge and hands-on experience in total station surveying. The main trainer expert is, Er. Amit Gupta, (Site Engineer, Smart City Project, Bhopal).

    Workshop Objectives

    The primary objectives of the workshop were to:

    1. Familiarize students with the various components and operation of total station machines.
    2. Instruct students on centering and leveling procedures to ensure accurate survey data.
    3. Teach students about topographic survey methods and data interpretation.
    4. Provide hands-on training in stakeout procedures, area and volume calculations.
    5. Demonstrate precise distance measurement techniques using total stations.

    Outcomes and Feedback
    The workshop received overwhelmingly positive feedback from the participants. Students gained a comprehensive understanding of total station surveying techniques, and the hands-on experience with the machines was particularly appreciated. The knowledge and skills acquired during the workshop are expected to be highly beneficial for their future careers in civil engineering and land surveying.

    Acknowledgments
    We extend our gratitude to Er. Amit Gupta for their excellent training and guidance throughout the workshop.

    Conclusion
    The 3-day Total Station Survey Workshop held at Technocrats Institute of Technology, Bhopal, Civil Engineering Department was a successful endeavor, equipping students with essential skills and knowledge in the field of civil engineering and land surveying. This workshop represents a significant step in ensuring that our students are well-prepared for the challenges and opportunities that lie ahead in their careers.

    No. of participants: 60

    Training on AutoCAD

    Topic AutoCAD
    Resource Person Ms. Kamna
    Duration 10/10/2022 to 22/10/2022
    Time 30 Hours
    Venue CAD Lab, TIT
    Participation Students of B.Tech. IIIrd & Vth Semester

    SUMMARY
    In collaboration with Elite Arch Group, the Department of Civil Engineering at Technocrats Institute of Technology, Bhopalprovided 10 Days of AutoCAD lab training sessions for Civil Engineering students. This training program’s major goal is to encourage students to plan and illustrate experiments in accordance with the guidelines provided, as well as to gauge their level of inventiveness. The Expert Ms. Kamna, shared with the students his knowledge of the field’s expectations for the designations of draughtsmen and interior designers. Additionally, he showed students some of his works and explained design principles and the use of fundamental tools with students. In total, 80 students have participated in this training program. The AutoCAD software used is one of the most commonly used software programs for civil engineering, It is used to create 2D and 3D models for the designed project. The tool allows engineers to instantly envision their designs, make any necessary revisions, and use it to create detailed building project drawings.

    OUTCOME
    The main goal of this course is to ignite students’ interest in civil-core software. By using this tool, the students will be able to produce 2D, 3D drawings & Design, which also makes it simpler and quicker for them to build and update digital 2D and 3D designs than they could manually.

  • ME – Coming Soon