Dr. Praveen Sankarasubramanian

@rmdresearchlabs.co.in

Independent Researcher and



                    

https://researchid.co/praveengrb
0

Scopus Publications

15

Scholar Citations

0

Scholar h-index

0

Scholar i10-index

Scopus Publications



  • Protection of Hazardous Places in Industries using Machine Learning
    Praveen Sankarasubramanian
    IEEE
    Extreme precautions must be observed to handle toxic wastes, radioactive substances, chemical raw materials, chemical wastes, and bio-products in different industries. Any malfunction in a dangerous traffic network can lead to serious accidents, deaths and / or serious damage. Direct monitoring and analysis, and preventive measures to prevent the spread of failures, can significantly reduce the recurrence of adverse effects. Current research suggests that detailed publicity and information on the latest developments in pipeline monitoring and research may help modernize the oil industry in the future. We also propose a framework to detect timely leakage in pipelines, especially in oil and gas sector.

  • Artificial intelligence-based detection system for hazardous liquid metal fire
    Praveen Sankarasubramanian and E. Ganesh

    Liquid metals are commonly used in chemical industries and nuclear reactors. Since liquid metals may be hazardous, they should be handled very carefully. Careless handling might cause an adverse effect and even disasters. Corrosion and pressure can deteriorate the structure that handles the liquid metals. Leakage of liquid metals can result in ecological disasters and can lead to a humanitarian crisis. Early warning systems, detection of the accident, and prompt steps taken after the incident are the three important phases of monitoring. Continuous monitoring and timely detection of risk reduce the impact caused by the leakage of liquid metal. At present, industries have sensors-based detection. This paper proposes an enhanced version of the existing system. Here, continuous monitoring uses sensors, the Internet of things (IoT), and an artificial intelligence-based system. In this paper, the conventional system is integrated with AI to identify indoor and open-air fire situations. This paper discusses different data collected and investigated data from the videos, sensors, other monitoring systems. And the false-positive results are reduced by using the proposed methodology.

  • Realtime Pipeline Fire Smoke Detection Using a Lightweight CNN Model
    Vaishnav Kumar Suresh Kumar and Praveen Sankarasubramanian

    Fire disasters due to pipeline leaks result in loss to life and property. Therefore, an expeditious model to detect smoke and fire is much needed. Even though there have been several types of research done on fire and smoke detection, most of these focuses on very generic datasets that boast good performance; the case of monitoring pipelines remotely necessitates a focused approach for enhanced performance for early detection. This paper attempts to develop a model specifically for this purpose and can be deployed more confidently in a pipeline environment. We have also customized the existing dataset by adding images of pipelines to bias the dataset and give a more confidence rate while predicting. Our proposed neural network architecture achieves higher accuracy, precision, recall, and F-measure. Also, the lightweight makes it easily deployable on embedded platforms as well. The performance of our model is evaluated against FireNet on our biased dataset, sounds very promising.

  • IoT based prediction for industrial ecosystem


RECENT SCHOLAR PUBLICATIONS

  • Enhancing precision in agriculture: A smart predictive model for optimal sensor selection through IoT integration
    P Sankarasubramanian
    Smart Agricultural Technology 10, 100749 2025

  • An efficient crack detection and leakage monitoring in liquid metal pipelines using a novel BRetN and TCK-LSTM techniques
    P Sankarasubramanian
    Multimedia Tools and Applications, 1-29 2024

  • ARTIFICIAL INTELLIGENCE AND NATURAL ALGORITHM
    P Sankarasubramanian
     2024

  • An optimal segmentation framework for early crack and fire detection using Potoo swarm optimization algorithm
    P Sankarasubramanian, E Ganesh
    Journal of Harbin Engineering University 44 (7), 217-233 2023

  • Protection of hazardous places in industries using machine learning
    P Sankarasubramanian
    2023 International Conference on Emerging Smart Computing and Informatics 2023

  • IoT based Optimal Liquid Metal Pipeline Damage Detection Using Hybrid Soft Computing Techniques
    P Sankarasubramanian, EN Ganesh
    NeuroQuantology 20 (5), 773 2022

  • CNN based intelligent framework to predict and detect fire
    P Sankarasubramanian, EN Ganesh
    NeuroQuantology 20 (5), 755-772 2022

  • Adaptive fire detection using cnn and image processing
    P Sankarasubramanian, EN Ganesh
    International Journal of Mechanical Engineering 7 (4) 2022

  • Realtime pipeline fire & smoke detection using a lightweight CNN model
    VKS Kumar, P Sankarasubramanian
    2021 IEEE International Conference on Machine Learning and Applied Network 2021

  • Effective Handling of Fluids and Liquid Metals using IoT
    P Sankarasubramanian
    International Journal of Institution of Safety Engineers (India) 3 (1) 2020

  • Prevent, Detect, Respond, Mitigate Liquid Sodium Leakage, and Fire Accidents using AI
    P Sankarasubramanian, EN Ganesh
    International Journal of Engineering and Advanced Technology 9 (5), 7-11 2020

  • Fire investigation and assessment using CNN and image processing
    P Sankarasubramanian, EN Ganesh
    Journal of Critical Reviews 7 (19), 9825-9830 2020

  • Industrial accident report analysis using natural language processing
    P Sankarasubramanian, EN Ganesh
    International Journal of Scientific & Technology Research 9 (6), 470-475 2020

  • Real Tıme AI, Computer Vısıon Based Framework To Detect And Prevent Lıquıd Metal Fıre Hazards
    P Sankarasubramanian, EN Ganesh
    International Journal of advanced science and technologies 28 (8), 3796-3085 2020

  • Ganesh. EN," Algorithm to Identify the Connection between Sentences,"
    P Sankarasubramanian
    International Journal Of Information And Computing Science 6 (7), 158-162 2019

  • Dr. EN Ganesh,“IoT Based Prediction for Industrial Ecosystem”
    P Sankarasubramanian
    International Journal of Engineering and Advanced Technology (IJEAT) ISSN 2019

  • Data Security and Replication on Cloud
    P Sankarasubramanian
     2017

  • ARTIFICIAL INTELLIGENCE AND NATURAL ALGORITHM
    P Sankarasubramanian

  • A Study Guide to Uncover Industrial Hazards
    P Sankarasubramanian, EN Ganesh

  • Fire Detection and Prediction Framework Using Vision Based System and Convolutional Neural Network
    P Sankarasubramanian, EN Ganesh

MOST CITED SCHOLAR PUBLICATIONS

  • Dr. EN Ganesh,“IoT Based Prediction for Industrial Ecosystem”
    P Sankarasubramanian
    International Journal of Engineering and Advanced Technology (IJEAT) ISSN 2019
    Citations: 129

  • Artificial Intelligence-Based Detection System for Hazardous Liquid Metal Fire
    P Sankarasubramanian, EN Ganesh
    Proceedings of the 15th INDIACom; INDIACom-2021; IEEE Conference ID: 51348
    Citations: 127

  • Realtime pipeline fire & smoke detection using a lightweight CNN model
    VKS Kumar, P Sankarasubramanian
    2021 IEEE International Conference on Machine Learning and Applied Network 2021
    Citations: 8

  • Effective Handling of Fluids and Liquid Metals using IoT
    P Sankarasubramanian
    International Journal of Institution of Safety Engineers (India) 3 (1) 2020
    Citations: 5

  • Real Tıme AI, Computer Vısıon Based Framework To Detect And Prevent Lıquıd Metal Fıre Hazards
    P Sankarasubramanian, EN Ganesh
    International Journal of advanced science and technologies 28 (8), 3796-3085 2020
    Citations: 5

  • Protection of hazardous places in industries using machine learning
    P Sankarasubramanian
    2023 International Conference on Emerging Smart Computing and Informatics 2023
    Citations: 4

  • Industrial accident report analysis using natural language processing
    P Sankarasubramanian, EN Ganesh
    International Journal of Scientific & Technology Research 9 (6), 470-475 2020
    Citations: 4

  • CNN based intelligent framework to predict and detect fire
    P Sankarasubramanian, EN Ganesh
    NeuroQuantology 20 (5), 755-772 2022
    Citations: 3

  • Prevent, Detect, Respond, Mitigate Liquid Sodium Leakage, and Fire Accidents using AI
    P Sankarasubramanian, EN Ganesh
    International Journal of Engineering and Advanced Technology 9 (5), 7-11 2020
    Citations: 3

  • Ganesh. EN," Algorithm to Identify the Connection between Sentences,"
    P Sankarasubramanian
    International Journal Of Information And Computing Science 6 (7), 158-162 2019
    Citations: 3

  • IoT based Optimal Liquid Metal Pipeline Damage Detection Using Hybrid Soft Computing Techniques
    P Sankarasubramanian, EN Ganesh
    NeuroQuantology 20 (5), 773 2022
    Citations: 2

  • Adaptive fire detection using cnn and image processing
    P Sankarasubramanian, EN Ganesh
    International Journal of Mechanical Engineering 7 (4) 2022
    Citations: 2

  • An optimal segmentation framework for early crack and fire detection using Potoo swarm optimization algorithm
    P Sankarasubramanian, E Ganesh
    Journal of Harbin Engineering University 44 (7), 217-233 2023
    Citations: 1

  • Fire investigation and assessment using CNN and image processing
    P Sankarasubramanian, EN Ganesh
    Journal of Critical Reviews 7 (19), 9825-9830 2020
    Citations: 1