HARSH KAPADIA

@nirmauni.ac.in

Assistant Professor, Electronics and Instrumentation Engineering Department
Institute of Technology, Nirma University

HARSH KAPADIA


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https://researchid.co/harsh291188
Prof Harsh K Kapadia is working as an Assistant Professor in Electronics and Instrumentation Engineering Department. He has more than 10 years of teaching and research experience. He has obtained MTech in Instrumentation and Control Engineering from Dharmsinh Desai University, Nadiad in 2012. He has published more than 15 research articles in national/international conferences. He has guided 7 post graduate students and several graduate students for their project work. He has filed two Indian patent along with other professors of the institute. He has successfully carried out three minor research projects funded by Nirma University. He is pursuing PhD on "Applications of advanced imaging techniques for concrete damage characterization". He has mentored Team Con-Sol-E for Mitsubishi Electric Cup ( A national level automation competition for students) which won the silver cup consecutively three times in a row (2017,2018 and 2019) and gold cup in 2020. His research areas include Image Pr

EDUCATION

Master of Technology in Instrumentation and Control Engineering

RESEARCH INTERESTS

Machine Vision Image Processing Embedded Systems
21

Scopus Publications

90

Scholar Citations

6

Scholar h-index

3

Scholar i10-index

Scopus Publications

  • Development of a Comprehensive Approach for Precise Positioning and Orientation of Multiple Mobile Robots in a Specified Formation Using Computer Vision and the Internet of Things
    Sneh Soni, Ansh Ruparel, Shreedhar Shah, Harsh Kapadia, Himanshu Patel
    Serbian Journal of Electrical Engineering, 2026
    The integration of Internet of Things (IoT) technologies into Multi- Robot Systems (MRS) has marked a significant advancement in the field of robotics and has opened up new avenues for innovation in robotics applications. By leveraging IoT technologies, robots in an MRS can be interconnected over a network, facilitating seamless communication and data exchange which can be used in various industrial as well as commercial applications. As manufacturing processes evolve towards increased automation and connectivity, MRS provides a versatile solution for tasks such as logistics, transportation, and collaborative assembly. This work presents a complete MRS architecture that combines Message Queue Telemetry Transport (MQTT) based wireless communication, overhead camera-assisted pose estimation using ArUco markers, a graphical control interface, and onboard sensing to achieve accurate multi-robot formation control. Unlike high-cost optical motion-capture systems like Vicon or infrastructure-dependent Ultra-Wide Band (UWB) localization, the proposed system attains centimeter-level accuracy using only a single overhead camera and low-power ESP32-based mobile robots. Real-time position and orientation feedback is computed using a Python-OpenCV pipeline, while MQTT ensures lightweight, low-latency communication between the master operating station and the robots. The Augmented Reality University of Cordoba (ArUco) markers are mounted on the top of each robot to give unique identity to each robot for easy identification and position orientation feedback. The system is experimentally validated across square, triangle, rectangle, and line formations. Each formation is executed over five independent trials, and statistical performance metrics in form of mean ? standard deviation demonstrate consistent accuracy and repeatability. A baseline comparison using pure encoder odometry shows substantially higher drift, confirming the benefit of closed-loop visual feedback. An ablation experiment disabling the magnetometer further quantifies its contribution to orientation stability. Additionally, a full timing and latency analysis covering frame rate, image-processing time, MQTT round-trip delay, and actuator reaction time verifies that the end-to-end control loop operates within real-time bounds. For the square formation task, the average position error remains below 10% relative to the robot?s chassis size and under 1% relative to the overall field dimensions. Similarly, the quantitative results and images are discussed for triangle, line and rectangle shape. The results demonstrate that the proposed MRS achieves robust, precise, and repeatable formation control with minimal hardware cost and infrastructure requirements. The effectiveness of the proposed algorithms and the overall MRS architecture for accurate positioning and orientation of mobile robots can be effectively utilized in a variety of industrial applications. Additionally, it can provide enhanced adaptability and flexibility in manufacturing, improved real-time communication through IoT, and feedback mechanisms.
  • A novel deep learning pipeline for coronary artery analysis in X-ray angiography
    Karan V. Padariya, Abhishek Raval, Pranay Soni, Harsh Kapadia
    Engineering Applications of Artificial Intelligence, 2025
  • Evaluation of Tilt Angle Estimation Techniques in Single-Axis Solar Trackers
    Harsh Kapadia, Ansh Ruparel, Kabir Jain, Himanshu Patel
    2025 2nd International Conference on Integration of Computational Intelligent System Icicis 2025, 2025
    This research presents a cost-effective, IoT-enabled single-axis solar tracking system. The detailed design of a single-axis solar tracking system for power plants is discussed in the paper. The primary focus is on calculating the solar PV Panel's tilt angles, making the system sensorless. Four tilt angle calculation methods, the true tracking and backtracking algorithm, the declination angle, the tangent angle, and the zenith angle, were implemented and evaluated in Python. The results of each algorithm were compared with the industry standard system advisor model (SAM) to assess accuracy. The approach based on the true tracking and backtracking algorithm demonstrated superior performance with minimal root mean square error (RMSE), ensuring optimal solar energy generation. Further optimisation of the tilt update frequency improved efficiency while balancing operational efforts. The results highlight the scalability and adaptability of the system, offering a practical solution to improve energy generation and cost effectiveness in solar farms.
  • Implementation of Computer Vision Technique for Crack Monitoring in Concrete Structure
    Harsh Kapadia, Paresh V. Patel, Jignesh B. Patel, Nikhil Kanani
    Journal of the Institution of Engineers India Series A, 2023
  • Convolutional neural network based improved crack detection in concrete cubes
    Harsh K Kapadia, Paresh V Patel, Jignesh B Patel
    International Journal of Computing and Digital Systems, 2023
    Advancement of imaging technology and computing resources make crack detection in concrete automated using a vision-based approach.The present work focuses on crack detection in laboratory-scale concrete cubes used for the characterization of concrete using the convolutional neural network.The major challenge in the said application is to remove inherent noise and dents from the uneven surface of the test cube.A laboratory-scale image acquisition setup was developed to acquire consistent images of concrete cubes.Inceptionv3 architecture was trained to detect the cracks in concrete cube surface images in the most accurate manner.The Inceptionv3 model was trained and validated using more than 80,000 crack and 80,000 non-crack images dataset prepared manually using the concrete cube surface images.Popular data augmentation techniques were used to generate the training dataset.An average of 97.49% accuracy and 7.38% cross-entropy are achieved in the training whereas 97.67% accuracy and 7.69% cross-entropy are achieved in the model validation.The training was carried out with a batch size of 100 and 5,000 epochs.An average accuracy of 99% has been achieved during the performance evaluation of crack detection on concrete cubes as presented in the results.The average values of precision, recall and F -score are obtained as 0.88, 0.98 and 0.93 respectively.
  • Non-Contact TDS Measurement by UV-VIS-NIR Spectrophotometric Analysis
    Devansh Rana, Simran Lulla, Harsh Kapadia, Ankure Dwivedi
    Proceedings of Conecct 2023 9th International Conference on Electronics Computing and Communication Technologies, 2023
    Water being the most important for existence of life and hence there exists a need to monitor it on a regular bases with the rising need. In our experimentation setup efforts have been made to minimize the unknowns and provide a standard as per the basic laws and provide a suitable environment to obtain repeatable readings. Light of the incident wavelength can affect the excitation of electrons in the atomic or molecular ground state to higher energy levels, giving rise to an absorbance at wavelengths specific to each molecule. The purpose of this study is to provide better insights to actual deployment of sensing systems alongside further development in the domain where existing piping infrastructure is disturbed to a minimum. Sensing system developed aims to nullify the existing shortcomings and put forward a solution to inline contactless TDS measurement on a repeatable basis by using machine learning based computations. This will provide added advantages like very low maintenance cost, specific elemental analysis, and easy integration. Further discussion on challenges, and improvements for a wider application scope is discussed.
  • Monitoring and Analysis of Surface Cracks in Concrete Using Convolutional Neural Network
    Harsh Kapadia, Nimit Soneji, Anirudha Rotti, Paresh V. Patel, Jignesh B. Patel
    Lecture Notes in Civil Engineering, 2023
  • Implementation of Master-Slave Communication Using MQTT Protocol
    Darsh Patel, Hitika Dalwadi, Hetvi Patel, Prasham Soni, Yash Battul, Harsh Kapadia
    Lecture Notes in Networks and Systems, 2023
  • Monitoring and analysis of crack developments in concrete using machine vision
    Journal of Structural Engineering India, 2022
  • Hybrid Computing System for Real-Time Implementation of a Convolutional Neural Network Application
    Pushpit Jain, Rishi Hiran, Harsh Kapadia, Paresh Patel, Jignesh B. Patel
    2022 International Conference for Advancement in Technology Iconat 2022, 2022
    There is a drastic increase in the usage of Artificial Intelligence, Machine Learning, and Deep Learning over the past decade, and innovative applications using these technologies are being developed. The development of such applications requires a tremendous amount of data and high computational power for training and deployment. Though cloud computing is a good way for development with the increasing amount of data, cloud computing proves out to be costly and slow. Edge computing devices have become the need of the hour, which could provide high computational power locally, saving on the costs of communicating with the server and providing a faster way of processing. The issue is addressed in the presented work with the use of commercially available edge computing devices. The developed method is tested for efficiency and computation speed. For the case study, the application of concrete crack detection using a convolutional neural network is considered. Transfer learning-based approach is adopted with the use of a pre-trained inception v3 CNN model. A concrete crack dataset is prepared for training and testing the model. In order to prove the computational efficiency of edge computing, two separated models were trained ad tested. A CPU standalone model and another model compatible with CPU and edge computing device were trained and tested. The experimental results show that the CPU with edge computing device requires much less computational time as compared to the CPU standalone mode and is at least 100 times faster in computation.
  • Review of in-line water quality measurement systems
    12th International Conference on Advances in Computing Control and Telecommunication Technologies Act 2021, 2021
  • Dry waste segregation using seamless integration of deep learning and industrial machine vision
    Harsh Kapadia, Alpesh Patel, Jignesh Patel, Shivam Patidar, Yash Richhriya, Darpan Trivedi, Priyank Patel, Meet Mehta
    Proceedings of Conecct 2021 7th IEEE International Conference on Electronics Computing and Communication Technologies, 2021
  • Development of low-cost embedded vision system with a case study on 1D barcode detection
    Vaishali Mishra, Harsh K. Kapadia, Tanish H. Zaveri, Bhanu Prasad Pinnamaneni
    Smart Innovation Systems and Technologies, 2019
  • An improved image pre-processing method for concrete crack detection
    Harsh Kapadia, Ripal Patel, Yash Shah, J. B. Patel, P. V. Patel
    Lecture Notes in Computational Vision and Biomechanics, 2019
  • Industrial internet of thing based smart process control laboratory: A case study on level control system
    Alpesh Patel, Rohit Singh, Jignesh Patel, Harsh Kapadia
    Smart Innovation Systems and Technologies, 2018
  • Data acquisition in wind power plant using SCADA
    Kumari Jyotsna, Ankit Sharma, Harsh Kapadia
    2017 International Conference on Intelligent Computing Instrumentation and Control Technologies Icicict 2017, 2017
  • SBHS: Some control investigations
    Priyabrata Majhi, Harsh K Kapadia, Alpesh I Patel, Jayesh J Barve, Divyesh R Raninga
    Nuicone 2015 5th Nirma University International Conference on Engineering, 2016
  • Image processing on embedded platform Android
    Sapan Thakker, Harsh Kapadia
    IEEE International Conference on Computer Communication and Control Ic4 2015, 2016
  • Measurement of wheel alignment using Camera Calibration and Laser Triangulation
    Jigar Senjalia, Parinda Pandya, Harsh Kapadia
    2013 Nirma University International Conference on Engineering Nuicone 2013, 2013
  • Evaluting the object recognition in real-time process
    Parinda Pandya, Jigar Senjalia, Harsh Kapadia
    2013 Nirma University International Conference on Engineering Nuicone 2013, 2013
  • Application of mean-shift algorithm for license plate localization
    Kinjal A. Shah, Harsh K. Kapadia, Vipul A. Shah, Maurya N. Shah
    2011 Nirma University International Conference on Engineering Current Trends in Technology Nuicone 2011 Conference Proceedings, 2011

RECENT SCHOLAR PUBLICATIONS

  • Development of a Comprehensive Approach for Precise Positioning and Orientation of Multiple Mobile Robots in a Specified Formation Using Computer Vision and the Internet of Things
    HP Sneh Soni, Ansh Ruparel, Shreedhar Shah, Harsh Kapadia
    SERBIAN JOURNAL OF ELECTRICAL ENGINEERING 23 (1), 21-55 , 2026
    2026
  • A novel deep learning pipeline for coronary artery analysis in X-ray angiography
    HK Karan V. Padariya, Abhishek Raval, Pranay Soni
    Engineering Applications of Artificial Intelligence 161 (Part C), 112217 , 2025
    2025
    Citations: 1
  • Evaluation of Tilt Angle Estimation Techniques in Single-Axis Solar Trackers
    H Kapadia, A Ruparel, K Jain, H Patel
    2025 2nd International Conference on Integration of Computational … , 2025
    2025
  • Non-Contact TDS Measurement by UV-VIS-NIR Spectrophotometric Analysis
    D Rana, S Lulla, H Kapadia, A Dwivedi
    2023 IEEE International Conference on Electronics, Computing and … , 2023
    2023
    Citations: 1
  • Implementation of Master-Slave Communication Using MQTT Protocol
    D Patel, H Dalwadi, H Patel, P Soni, Y Battul, H Kapadia
    Next Generation Systems and Networks: Proceedings of BITS EEE CON 2022 641, 11 , 2023
    2023
    Citations: 3
  • Implementation of computer vision technique for crack monitoring in concrete structure
    H Kapadia, PV Patel, JB Patel, N Kanani
    Journal of The Institution of Engineers (India): Series A 104 (1), 111-123 , 2023
    2023
    Citations: 3
  • Convolutional Neural Network Based Improved Crack Detection In Concrete Cubes
    HK Kapadia, PV Patel, JB Patel
    International Journal of Computing and Digital Systems 13 (1), 341-352 , 2023
    2023
    Citations: 3
  • Monitoring and analysis of crack developments in concrete using machine vision
    JBP Harsh K. Kapadia, Paresh V. Patel
    Journal of Structural Engineering 49 (3), 204-222 , 2022
    2022
    Citations: 2
  • Monitoring and Analysis of Surface Cracks in Concrete Using Convolutional Neural Network
    H Kapadia, N Soneji, A Rotti, PV Patel, JB Patel
    International Conference on Structural Engineering and Construction … , 2022
    2022
    Citations: 1
  • ACCURATE CRACK IDENTIFICATION ON THE CONCRETE STRUCTURE USING CONVOLUTIONAL NEURAL NETWORK
    JBP Harsh Kapadia, Nikhil Kanani, Paresh V Patel
    3RD INTERNATIONAL CONFERENCE ON NEW HORIZONS IN GREEN CIVIL ENGINEERING … , 2022
    2022
  • Hybrid Computing System for Real-Time Implementation of a Convolutional Neural Network Application
    P Jain, R Hiran, H Kapadia, P Patel, JB Patel
    2022 International Conference for Advancement in Technology (ICONAT) , 2022
    2022
  • Advanced imaging techniques for damage characterization of concrete
    HK Kapadia
    Institute of Technology , 2022
    2022
  • Implementation of computer vision technique for crack monitoring in concrete structure
    HK Nikhil Kanani, Paresh Patel
    36th Indian Engineering Congress , 2021
    2021
  • Convolutional neural network based technique for accurate detection of cracks in concrete
    HK Nikhil Kanani, Paresh Patel
    International conference on research and development in civil engineering , 2021
    2021
  • Dry waste segregation using seamless integration of deep learning and industrial machine vision
    H Kapadia, A Patel, J Patel, S Patidar, Y Richhriya, D Trivedi, P Patel, ...
    2021 IEEE International Conference on Electronics, Computing and … , 2021
    2021
    Citations: 11
  • Review of In-line Water Quality Measurement Systems
    D Rana, H Kapadia
    Grenze International, NCR, Delhi 7 (1), 63-68 , 2021
    2021
    Citations: 1
  • Review of In-line Water Quality Measurement Systems
    HK Devansh Rana
    Eleventh International Joint Conference on Advances in Engineering and … , 2020
    2020
  • Development of Low-Cost Embedded Vision System with a Case Study on 1D Barcode Detection
    V Mishra, HK Kapadia, TH Zaveri, BP Pinnamaneni
    Information and Communication Technology for Intelligent Systems … , 2018
    2018
    Citations: 1
  • An Improved Image Pre-processing Method for Concrete Crack Detection
    H Kapadia, R Patel, Y Shah, JB Patel, PV Patel
    International Conference on ISMAC in Computational Vision and Bio … , 2018
    2018
    Citations: 5
  • Data acquisition in wind power plant using SCADA
    K Jyotsna, A Sharma, H Kapadia
    2017 International Conference on Intelligent Computing, Instrumentation and … , 2017
    2017
    Citations: 7

MOST CITED SCHOLAR PUBLICATIONS

  • Application of Hough transform and sub-pixel edge detection in 1-D barcode scanning
    H Kapadia, A Patel
    IJAREEIE , 2013
    2013
    Citations: 16
  • Dry waste segregation using seamless integration of deep learning and industrial machine vision
    H Kapadia, A Patel, J Patel, S Patidar, Y Richhriya, D Trivedi, P Patel, ...
    2021 IEEE International Conference on Electronics, Computing and … , 2021
    2021
    Citations: 11
  • Measurement of wheel alignment using Camera Calibration and Laser Triangulation
    J Senjalia, P Pandya, H Kapadia
    2013 Nirma University International Conference on Engineering (NUiCONE), 1-5 , 2013
    2013
    Citations: 11
  • Data acquisition in wind power plant using SCADA
    K Jyotsna, A Sharma, H Kapadia
    2017 International Conference on Intelligent Computing, Instrumentation and … , 2017
    2017
    Citations: 7
  • Image processing on embedded platform Android
    S Thakker, H Kapadia
    2015 International Conference on Computer, Communication and Control (IC4), 1-6 , 2015
    2015
    Citations: 6
  • Evaluting the object recognition in real-time process
    P Pandya, J Senjalia, H Kapadia
    2013 Nirma University International Conference on Engineering (NUiCONE), 1-6 , 2013
    2013
    Citations: 6
  • Application of Mean-Shift algorithm for license plate localization
    KA Shah, HK Kapadia, VA Shah, MN Shah
    2011 Nirma University International Conference on Engineering, 1-5 , 2011
    2011
    Citations: 6
  • An Improved Image Pre-processing Method for Concrete Crack Detection
    H Kapadia, R Patel, Y Shah, JB Patel, PV Patel
    International Conference on ISMAC in Computational Vision and Bio … , 2018
    2018
    Citations: 5
  • Implementation of Master-Slave Communication Using MQTT Protocol
    D Patel, H Dalwadi, H Patel, P Soni, Y Battul, H Kapadia
    Next Generation Systems and Networks: Proceedings of BITS EEE CON 2022 641, 11 , 2023
    2023
    Citations: 3
  • Implementation of computer vision technique for crack monitoring in concrete structure
    H Kapadia, PV Patel, JB Patel, N Kanani
    Journal of The Institution of Engineers (India): Series A 104 (1), 111-123 , 2023
    2023
    Citations: 3
  • Convolutional Neural Network Based Improved Crack Detection In Concrete Cubes
    HK Kapadia, PV Patel, JB Patel
    International Journal of Computing and Digital Systems 13 (1), 341-352 , 2023
    2023
    Citations: 3
  • Monitoring and analysis of crack developments in concrete using machine vision
    JBP Harsh K. Kapadia, Paresh V. Patel
    Journal of Structural Engineering 49 (3), 204-222 , 2022
    2022
    Citations: 2
  • Industrial Internet of Thing Based Smart Process Control Laboratory: A Case Study on Level Control System
    A Patel, R Singh, J Patel, H Kapadia
    International Conference on Information and Communication Technology for … , 2017
    2017
    Citations: 2
  • Development of a non-linear process control test bench and empirical investigation of control performance
    H Bhadauriya, H Kapadia, JB Patel, A Patel
    International Journal of Advanced Technology and Engineering Exploration 3 … , 2016
    2016
    Citations: 2
  • A novel deep learning pipeline for coronary artery analysis in X-ray angiography
    HK Karan V. Padariya, Abhishek Raval, Pranay Soni
    Engineering Applications of Artificial Intelligence 161 (Part C), 112217 , 2025
    2025
    Citations: 1
  • Non-Contact TDS Measurement by UV-VIS-NIR Spectrophotometric Analysis
    D Rana, S Lulla, H Kapadia, A Dwivedi
    2023 IEEE International Conference on Electronics, Computing and … , 2023
    2023
    Citations: 1
  • Monitoring and Analysis of Surface Cracks in Concrete Using Convolutional Neural Network
    H Kapadia, N Soneji, A Rotti, PV Patel, JB Patel
    International Conference on Structural Engineering and Construction … , 2022
    2022
    Citations: 1
  • Review of In-line Water Quality Measurement Systems
    D Rana, H Kapadia
    Grenze International, NCR, Delhi 7 (1), 63-68 , 2021
    2021
    Citations: 1
  • Development of Low-Cost Embedded Vision System with a Case Study on 1D Barcode Detection
    V Mishra, HK Kapadia, TH Zaveri, BP Pinnamaneni
    Information and Communication Technology for Intelligent Systems … , 2018
    2018
    Citations: 1
  • SBHS: Some control investigations
    P Majhi, HK Kapadia, AI Patel, JJ Barve, DR Raninga
    2015 5th Nirma University International Conference on Engineering (NUiCONE), 1-6 , 2015
    2015
    Citations: 1