VALAI GANESH S

@ritrjpm.ac.in

Assistant Professor and Department of Mechanical Engineering
Ramco Institute of Technology

VALAI GANESH S


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https://researchid.co/valaiganesh

RESEARCH INTERESTS

Robotics
Mechatronics
Automation
Artificial Intelligence
Machine Learning
17

Scopus Publications

48

Scholar Citations

4

Scholar h-index

Scopus Publications

  • Assessment of Higher-Order and Critical Thinking Skills in Mini and Capstone Projects: A CDIO and OBE-Aligned Framework in Undergraduate Mechanical Engineering Education
    Rajakarunakaran S., J. Jerold John Britto, Valai Ganesh S.
    Journal of Engineering Education Transformations, 2026
    In this paper, we propose the conceptual framework on how higher-order and critical thinking skills in undergraduate mechanical engineering can be measured in the context of authentic and project-based learning based on mini and capstone projects. Based on CDIO (Conceive Design Implement Operate) and Outcome-Based Education (OBE), the framework uses analytically built rubrics with extensively designed analytic measurement and multidimensional assessment to continuously assess cognitive skills such as analysis, synthesis, evaluation, and creative problem-solving. The method will help it align with specified course and program outcomes, allowing transparent, fair, and actionable assessment practices.
  • Sustainable electronic waste management framework for academic institutions in India
    S. Valai Ganesh, V. Suresh, S. Rajakarunakaran, V. Suryakumar
    Scientific Reports, 2025
    Technology is increasingly used in schools to teach, study, and organise. Technology use has increased e-waste. As "electronic waste" or "e-waste," old laptops, desktops, projectors, and other devices contain hazardous components that can harm the environment if discarded improperly. This study examines the challenges learning institutions face in handling e-waste without compromising efficiency, including the need to stay current, insufficient funds to repair equipment, and a lack of knowledge on how to dispose of it. To overcome these obstacles, this article proposed a shared solution: a sustainable collaboration to manage electronic waste. e-waste data collection and analysis are the foundation of this framework. Of 452 electrical products, 32.1% were older than 5 years and 34.1% needed repair or replacement. On-site recycling offers a 90% material recovery rate and a 10,000 yearly profit after operational expenses, making it superior than external recycling (210,000 vs. 7,000). Real-time monitoring, automated reporting, and decision-support tools make the suggested concept reproducible for sustainable e-waste management in learning institutions. The suggested framework would reduce carbon emissions by 5-7 metric tonnes and salvage 15 tonnes of valuable materials annually. It also estimates the cost of delivering electronic waste to merchants and compares it to the cost of constructing an e-waste recycling centre in a learning institution. By working together, educational institutions may lessen their environmental effect and be responsible technology guardians for future generations.
  • EXPLORING SUSTAINABLE FUTURES: STRATEGIC TRANSITIONS IN INDIA'S URBAN WASTE SCENARIO - A COMPREHENSIVE REVIEW
    Valai Ganesh Sankararamasubramanian, Suresh Vaikuntam, Godwin Barnabas Solomon, Rajakarunakaran Sivaprakasam
    Environmental Engineering and Management Journal, 2025
  • Predictive Analysis and Data-Driven Approaches for Developing Sustainable Municipal Solid Waste Management Strategies in Smart Cities: An Urban Analysis of Madurai
    Valai Ganesh S., Suresh V., Godwin Barnabas S.
    Iranian Journal of Chemistry and Chemical Engineering, 2025
    The development of predictive models for waste handling remains the primary barrier to sustainable waste management in Madurai Smart City for accurate policy formulation. The research brought together quantitative data collected through stakeholder interviews of waste policies and quantitative methods measuring waste collection rates using population projections and machine learning algorithms. XG Gradient Boosting (a machine learning technology) generated the most precise outcomes when we evaluated our models because it forecasted organic waste with a coefficient of determination (R²) of 0.91 and inorganic waste with R² = 0.91, surpassing traditional Linear Regression models that reported organic waste prediction accuracy at R² = 0.867 and inorganic waste prediction at R² = 0.577. The temporal evaluation revealed seasonal patterns. Cultural events generated waste volumes that were 30% higher than normal yearly rates. The spatial assessment results show that Zones 1 and 4 are waste generation priority areas requiring a 75% capacity expansion during the next decade. Waste production in Madurai is projected to reach 1,000 metric tons each day by 2030, representing an increase of 54% from the present levels. An assessment of the findings indicates that the processing capacity should be expanded to 350 Tons Per Day (TPD), and waste segregation policies must implement zone-based rules while optimizing delivery routes to decrease vehicle fuel usage by 15-20%. The data-based structure provides the groundwork for constructing enduring waste management facilities throughout Madurai and similar fast-developing urban territories.
  • Transforming student assessments in the era of machine learning: Balancing innovation and ethics
    S. Valai Ganesh, V. Suresh, S. Rajakarunakaran, L. Ganesan, V. Suryakumar
    Driving Quality Education Through AI and Data Science, 2025
    Machine learning algorithms are now being used to improve personalised student assessments in higher education. This chapter examines the benefits and ethical considerations of using these algorithms to develop personalised and customised testing experiences. Through the analysis of vast datasets, machine learning algorithms may offer useful insights into student progress and identify specific areas that require work. This allows educators to customise their teaching methods to meet the individual needs of each student. Nevertheless, the implementation of these technologies gives rise to ethical considerations pertaining to privacy, bias, and openness. This chapter examines the difficulties associated with machine learning in personalised student assessments and proposes creative methods to ensure fair and responsible use. The objective of the discussion is to find a middle ground between utilising the potential advantages of these algorithms and upholding ethical principles, thereby promoting a more efficient and inclusive learning environment in higher education.
  • COMMERCIALIZATION OF WASTE TYRE USING A SIMPLE RECYCLING PROCESS
    Godwin Barnabas, Arun Vasantha Geethan, Valai Ganesh
    Environmental Engineering and Management Journal, 2025
    The inability of tires to biodegrade harms the environment and the entire ecosystem.Sometimes, discarding or keeping these old tyres in one location can turn them into a breeding ground for germs, insects, and mosquitoes, leading to infectious illnesses.Wood waste is compressed into crumb rubber as a powder using hot pressing.The scrap wood and crumb rubber used to create the woodrubber composite have good mechanical qualities.After completing the tensile, tear, and thermal testing, it was discovered that the tensile strength is of the commercial material is 7.848 MPa, which is closer to that of virgin rubber (10 MPa).Over 120 N is Known to be the yield/break force.The yield elongation and %age elongation are determined to be close to 180%, similar to those of virgin rubber.In addition to its mechanical characteristics, it exhibits water absorption rates closer to 1 part in a thousand cycles and extremely little chemical erosion, similar to virgin rubber.The manufactured recycled crumb rubber is also suitable for commercial applications, including flooring, sound insulation, heavy-duty performance, and vibration absorption due to the aforementioned qualities.
  • Advancements in mechatronic systems for manufacturing, robotics, and automation Yaskawa Motoman GP12 robot applications
    S. Valai Ganesh, Vikram Suresh, S. Godwin Barnabas, S. Rajakarunakaran
    Mechatronics Concepts Tools Applications and New Trends, 2025
    Modern mechatronics has transformed automation, robotics, and production, resulting in higher accuracy, flexibility, and efficiency. This chapter examines the evolution of mechatronic systems with particular reference to the manufacturing applications of the Yaskawa Motoman GP12 robot. An overview of the capabilities of the Motoman GP12 robot is given at the beginning of this chapter. The discussion of mechanical engineering in the manufacturing sector is then expanded upon. The book then discusses the application of bots in flexible production systems, with a particular emphasis on modular mechatronic systems and reconfigurable manufacturing. This case study demonstrates how to set up a versatile production system using the Motoman GP12 robot. This chapter contains more information about the programming, control, and mechatronic design issues associated with integrating the Motoman GP12 robot into the manufacturing process. The effectiveness of a production technique using the GP12 robot is tested in a controlled trial. The use of robots in high-precision manufacturing procedures is examined in this book. It emphasises potential issues as well as upgraded motors, sensors, and control systems. A Motoman GP12 robot assembly method is planned and verified in this case study. The technology that enables the Motoman GP12 robot to be used in complicated mechatronic production is the main topic of discussion. Among these technologies are wireless communication protocols, machine learning algorithms for adaptive control, and sensor fusion methods. Examining future trends and challenges, this chapter discusses Industry 4.0, the potential impact of AI and the IoT on mechatronic systems using the Motoman GP12 robot, and the challenges in implementing advanced mechatronic solutions in industry. The Motoman GP12 robot is highlighted in this chapter together with important results regarding the development and application of mechatronic systems in the manufacturing industry. It also offers ideas for future studies and developments.
  • A critical analysis and prediction of heat transfer and flow characteristics in the sudden expansion channel with square block using machine learning
    Murugashri V, Balavignesh P, Rahul P, Ramanathan Seranthian, Valai Ganesh S.
    Numerical Heat Transfer Part B Fundamentals, 2025
    In this article, the numerical simulation of a 2D flow in an SEC (Sudden expansion channel) with a square block as a VG (Vortex generator) is performed using FVM (Finite volume method) in Ansys FLUENT 2022 R1. A square block of 5x5 mm is deployed in the SEC having ER = 2 (Expansion ratio). The impact of vortex dynamics on heat interaction amplification and fluid flow attributes are observed for various values of Re ranging from 117 to 583. The vortex dynamics for q = 500, 750, and 1000 W/m2 have been thoroughly investigated for different positions of the square block. The working fluid is water that flows in an SEC with a square block at the step, 10, 20, 30, and 40 mm. Machine learning algorithms were utilized to forecast the most advantageous conditions of input variables, including block position, heat flux (q), and Re number, in order to achieve the highest possible overall performance factor (OPF). It is predicted that the maximum OPF is achieved for Re = 640 when the block is placed 30 mm from the step on the bottom wall.
  • Adaptive Learning Technologies: Navigating the Road from Hype to Reality
    S. Valai Ganesh, M. Gomathy Nayagam, V. Suresh, S. Rajakarunakaran, B. Bensujin
    Multimodal Generative AI, 2025
  • Innovative solid waste management strategies for smart cities in Tamil Nadu: challenges, technological solutions, and sustainable prospects
    S. Valai Ganesh, V. Suresh, S. Godwin Barnabas, S. Rajakarunakaran
    Discover Applied Sciences, 2024
    This study focuses on the challenges, technological solutions, and sustainability prospects of solid waste management practices in eleven smart cities in Tamil Nadu, India, through a case study. It was through a systematic review and stakeholder interviews that we assessed the current waste management infrastructure, collection, and processing capabilities in these cities. The analysis concluded that measures for waste segregation remain poor, with collection efficiencies ranging between 80 and 100% and segregation rates across the sampled cities from below 50% to 100% for varying cities. Constraints also include poor infrastructure, lack of public awareness, and financial problems. We develop an integrated waste management framework that advocates source segregation, localized processing, and waste-to-energy plans. The study has shown that the efficient use of smart technologies, the development of public–private alliances, and the principles of the circular economy would significantly enhance the effectiveness of waste management practices in the smart cities of Tamil Nadu. Policy makers and urban planners focused on ameliorating municipal solid waste management systems in fast-growing urban areas can benefit from these findings.
  • Building smart bot designs for library assistance
    Robotics and Automation in Healthcare Advanced Applications, 2024
  • A review on implementation of Kanban system in various process industries
    Godwin Barnabas Solomon, Sridharan Surendran, Ragul Ramesh, Valai Ganesh Sankararamasubramanian, Satish Pandian Ganapathy, Prasad Deivendran
    Aip Conference Proceedings, 2023
  • APPLICATION of DECISION-MAKING ALGORITHMS in the LANDFILL SITE SELECTION
    Godwin Barnabas, Arun Vasantha Geethan, Valai Ganesh, MKV Karthikeyan, Chrispin Das
    Environmental Engineering and Management Journal, 2023
  • Static and dynamic activities prediction of human using machine and deep learning models
    S. Valai Ganesh, Mohit Agarwal, Suneet Kr. Gupta, S. Rajakarunakaran
    Lecture Notes in Networks and Systems, 2021
  • Role of Modern Technologies and Internet of Things in the Field of Solid Waste Management
    S.Godwin Barnabas, K.Arun vasantha Geethan, S.Valai Ganesh, S. Rajakarunakaran, P.Sabarish Kumar
    International Journal of Computers Communications and Control, 2021
  • Development of medical physio device for stroke patients
    S. Godwin Barnabas, S. Valai Ganesh, V. Sivakumar, P. Muthukumar, A. Dhinesh Raja, K. Hariharan
    Materials Today Proceedings, 2021
  • Development of self governed flashing system in automotives using AI technique
    N. Sankarachelliah, V. Rijith Kumar, P. Senthilram, S. Valai Ganesh, T. Selva Sundar, S. Godwin Barnabas, S. Rajakarunakaran
    Lecture Notes in Networks and Systems, 2021

RECENT SCHOLAR PUBLICATIONS

  • Sustainable electronic waste management framework for academic institutions in India
    S Valai Ganesh, V Suresh, S Rajakarunakaran, V Suryakumar
    Scientific Reports 15 (1), 40550 , 2025
    2025
    Citations: 1
  • EXPLORING SUSTAINABLE FUTURES: STRATEGIC TRANSITIONS IN INDIA'S URBAN WASTE SCENARIO-A COMPREHENSIVE REVIEW.
    VG Sankararamasubramanian, S Vaikuntam, GB Solomon, ...
    Environmental Engineering & Management Journal (EEMJ) 24 (9) , 2025
    2025
  • Predictive Analysis and Data-Driven Approaches for Developing Sustainable Municipal Solid Waste Management Strategies in Smart Cities: An Urban Analysis of Madurai
    SVGBS Valai Ganesh S
    Iranian Journal of Chemistry and Chemical Engineering 44 (7), 1976-1993 , 2025
    2025
    Citations: 9
  • Adaptive Learning Technologies: Navigating the Road from Hype to Reality
    BB S. Valai Ganesh, M. Gomathy Nayagam, V. Suresh, S. Rajakarunakaran
    Multimodal Generative AI, 79-113 , 2025
    2025
    Citations: 8
  • Multimodal generative AI
    A Singh
    Springer , 2025
    2025
    Citations: 5
  • Advancements in mechatronic systems for manufacturing, robotics, and automation: Yaskawa Motoman GP12 robot applications
    SV Ganesh, V Suresh, SG Barnabas, S Rajakarunakaran
    Mechatronics, 116-140 , 2025
    2025
  • COMMERCIALIZATION OF WASTE TYRE USING A SIMPLE RECYCLING PROCESS
    SVG Godwin Barnabas, Arun Vasantha Geethan
    Environmental Engineering and Management Journal 24 (1), 63-77 , 2025
    2025
  • Transforming Student Assessments in the Era of Machine Learning: Balancing Innovation and Ethics
    SV Ganesh, V Suresh, S Rajakarunakaran, L Ganesan, V Suryakumar
    Driving Quality Education Through AI and Data Science, 383-408 , 2025
    2025
  • Innovative solid waste management strategies for smart cities in Tamil Nadu: challenges, technological solutions, and sustainable prospects
    SV Ganesh, V Suresh, SG Barnabas, S Rajakarunakaran
    Discover Applied Sciences 6 (12), 660 , 2024
    2024
    Citations: 7
  • Building Smart Bot Designs for Library Assistance
    SV Ganesh, V Suresh, SG Barnabas, S Rajakarunakaran
    Robotics and Automation in Healthcare, 21-44 , 2024
    2024
  • A Critical Analysis and Prediction of Heat Transfer and Flow Characteristics in the Sudden Expansion Channel with Square Block Using Machine Learning
    VGS V Murugashri, Balavignesh P, Rahul P, Ramanathan Seranthian
    Numerical Heat Transfer, Part B: Fundamentals, 1-25 , 2024
    2024
  • A review on implementation of Kanban system in various process industries
    GB Solomon, S Surendran, R Ramesh, VG Sankararamasubramanian, ...
    AIP Conference Proceedings 2831 (1), 070001 , 2023
    2023
    Citations: 4
  • APPLICATION OF DECISION-MAKING ALGORITHMS IN THE LANDFILL SITE SELECTION.
    GS Barnabas, AV Geethan, VS Ganesh, MKV Karthikeyan, CM Das
    Environmental Engineering & Management Journal (EEMJ) 22 (9) , 2023
    2023
    Citations: 1
  • VITAL ROLE OF RECENT TECHNOLOGIES IN SORTING DIFFERENT SOLID WASTE MATERIALS IN RECYCLING PROCESS
    AVG Kathiresan, GB Solomon, VG Sankararamasubramanian, ...
    FEB-FRESENIUS ENVIRONMENTAL BULLETIN, 5271 , 2022
    2022
  • Obtaining the zero landfill for End of Life of automotive components using efficient recycling and reusing approach
    KAV Geethan, SG Barnabas, VA Suyamburajan, SV Ganesh
    Feb-Fresenius Environmental Bulletin, 9821 , 2022
    2022
    Citations: 2
  • Role of modern technologies and internet of things in the field of solid waste management
    SG Barnabas, KA vasantha Geethan, SV Ganesh, S Rajakarunakaran, ...
    INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL 16 (5) , 2021
    2021
    Citations: 4
  • Development of Self Governed Flashing System in Automotives Using AI Technique
    N Sankarachelliah, V Rijith Kumar, P Senthilram, S Valai Ganesh, ...
    Innovations in Computer Science and Engineering: Proceedings of 8th ICICSE … , 2021
    2021
    Citations: 1
  • Static and dynamic activities prediction of human using machine and deep learning models
    S Valai Ganesh, M Agarwal, SK Gupta, S Rajakarunakaran
    Innovations in Computer Science and Engineering: Proceedings of 8th ICICSE, 1-7 , 2021
    2021
    Citations: 4
  • Innovations in Computer Science and Engineering: Proceedings of 8th ICICSE
    HS Saini, R Sayal, A Govardhan, R Buyya
    Springer , 2021
    2021
    Citations: 1
  • Development of Self Governed Flashing System in Automotives Using AI
    TS Sundar, SG Barnabas, S Rajakarunakaran
    Innovations in Computer Science and Engineering: Proceedings of 8th ICICSE, 327 , 2021
    2021

MOST CITED SCHOLAR PUBLICATIONS

  • Predictive Analysis and Data-Driven Approaches for Developing Sustainable Municipal Solid Waste Management Strategies in Smart Cities: An Urban Analysis of Madurai
    SVGBS Valai Ganesh S
    Iranian Journal of Chemistry and Chemical Engineering 44 (7), 1976-1993 , 2025
    2025.0
    Citations: 9
  • Adaptive Learning Technologies: Navigating the Road from Hype to Reality
    BB S. Valai Ganesh, M. Gomathy Nayagam, V. Suresh, S. Rajakarunakaran
    Multimodal Generative AI, 79-113 , 2025
    2025.0
    Citations: 8
  • Innovative solid waste management strategies for smart cities in Tamil Nadu: challenges, technological solutions, and sustainable prospects
    SV Ganesh, V Suresh, SG Barnabas, S Rajakarunakaran
    Discover Applied Sciences 6 (12), 660 , 2024
    2024.0
    Citations: 7
  • Multimodal generative AI
    A Singh
    Springer , 2025
    2025.0
    Citations: 5
  • A review on implementation of Kanban system in various process industries
    GB Solomon, S Surendran, R Ramesh, VG Sankararamasubramanian, ...
    AIP Conference Proceedings 2831 (1), 070001 , 2023
    2023.0
    Citations: 4
  • Role of modern technologies and internet of things in the field of solid waste management
    SG Barnabas, KA vasantha Geethan, SV Ganesh, S Rajakarunakaran, ...
    INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL 16 (5) , 2021
    2021.0
    Citations: 4
  • Static and dynamic activities prediction of human using machine and deep learning models
    S Valai Ganesh, M Agarwal, SK Gupta, S Rajakarunakaran
    Innovations in Computer Science and Engineering: Proceedings of 8th ICICSE, 1-7 , 2021
    2021.0
    Citations: 4
  • Obtaining the zero landfill for End of Life of automotive components using efficient recycling and reusing approach
    KAV Geethan, SG Barnabas, VA Suyamburajan, SV Ganesh
    Feb-Fresenius Environmental Bulletin, 9821 , 2022
    2022.0
    Citations: 2
  • Sustainable electronic waste management framework for academic institutions in India
    S Valai Ganesh, V Suresh, S Rajakarunakaran, V Suryakumar
    Scientific Reports 15 (1), 40550 , 2025
    2025.0
    Citations: 1
  • APPLICATION OF DECISION-MAKING ALGORITHMS IN THE LANDFILL SITE SELECTION.
    GS Barnabas, AV Geethan, VS Ganesh, MKV Karthikeyan, CM Das
    Environmental Engineering & Management Journal (EEMJ) 22 (9) , 2023
    2023.0
    Citations: 1
  • Development of Self Governed Flashing System in Automotives Using AI Technique
    N Sankarachelliah, V Rijith Kumar, P Senthilram, S Valai Ganesh, ...
    Innovations in Computer Science and Engineering: Proceedings of 8th ICICSE … , 2021
    2021.0
    Citations: 1
  • Innovations in Computer Science and Engineering: Proceedings of 8th ICICSE
    HS Saini, R Sayal, A Govardhan, R Buyya
    Springer , 2021
    2021.0
    Citations: 1
  • Design and Development of Pneumatic Articulated Robot For Palletizing Operations
    B Ramkumar, K Venkatesh, R Ramesh, SV Ganesh
    International Journal of Emerging Technology in Computer Science … , 0
    Citations: 1
  • EXPLORING SUSTAINABLE FUTURES: STRATEGIC TRANSITIONS IN INDIA'S URBAN WASTE SCENARIO-A COMPREHENSIVE REVIEW.
    VG Sankararamasubramanian, S Vaikuntam, GB Solomon, ...
    Environmental Engineering & Management Journal (EEMJ) 24 (9) , 2025
    2025.0
  • Advancements in mechatronic systems for manufacturing, robotics, and automation: Yaskawa Motoman GP12 robot applications
    SV Ganesh, V Suresh, SG Barnabas, S Rajakarunakaran
    Mechatronics, 116-140 , 2025
    2025.0
  • COMMERCIALIZATION OF WASTE TYRE USING A SIMPLE RECYCLING PROCESS
    SVG Godwin Barnabas, Arun Vasantha Geethan
    Environmental Engineering and Management Journal 24 (1), 63-77 , 2025
    2025.0
  • Transforming Student Assessments in the Era of Machine Learning: Balancing Innovation and Ethics
    SV Ganesh, V Suresh, S Rajakarunakaran, L Ganesan, V Suryakumar
    Driving Quality Education Through AI and Data Science, 383-408 , 2025
    2025.0
  • Building Smart Bot Designs for Library Assistance
    SV Ganesh, V Suresh, SG Barnabas, S Rajakarunakaran
    Robotics and Automation in Healthcare, 21-44 , 2024
    2024.0
  • A Critical Analysis and Prediction of Heat Transfer and Flow Characteristics in the Sudden Expansion Channel with Square Block Using Machine Learning
    VGS V Murugashri, Balavignesh P, Rahul P, Ramanathan Seranthian
    Numerical Heat Transfer, Part B: Fundamentals, 1-25 , 2024
    2024.0
  • VITAL ROLE OF RECENT TECHNOLOGIES IN SORTING DIFFERENT SOLID WASTE MATERIALS IN RECYCLING PROCESS
    AVG Kathiresan, GB Solomon, VG Sankararamasubramanian, ...
    FEB-FRESENIUS ENVIRONMENTAL BULLETIN, 5271 , 2022
    2022.0