Real-Time Wild Animal Intrusion Detection and Repellent System Using YOLOv5n and Predator Scent Lal Raja Singh R, Sandeep Krishnaa S, Shreenikesh V Proceedings of the 6th International Conference on Inventive Research in Computing Applications Icirca 2025, 2025 In recent days, the issue of human-wildlife conflict, especially involving wild boars, has become a increasing concern in rural and forest-bordering agricultural regions. Traditional methods like fencing, manual guarding, or noise scare devices are not very effective always, and also requires human effort or it may harm the animals in some cases. Some systems using automation are developed, but they mostly lack in accurate detection or fast response time. In this project, we proposed a non-lethal, automatic wild animal detection and repulsion system based on real-time object detection using YOLOv5n model and high-frequency audio deterrent system. The system uses a Raspberry Pi, PIR sensor and camera to detect movement and identify wild boars using trained YOLOv5n model. Once detection is confirmed, the system triggers a high-frequency sound using amplifier and also sends alert to the farmer via GSM module and cloud. The model was trained on a custom dataset and shows decent accuracy with improving performance metrics during training. This system reduce human-animal conflicts and crop damages, and also helps to avoid harming the animals, so it is both effective and ethical.
Digital Twin Modelling and Rul Estimation of a Battery Powered Motor System in Matlab Lal Raja Singh R, Chandru G, Ganesh Kumar R, Gokam Gokul 2025 4th International Conference on Smart Technologies and Systems for Next Generation Computing Icstsn 2025, 2025 The increasing adoption of electric vehicles and renewable energy systems has placed a strong emphasis on accurate prediction of battery lifetime to ensure safety, efficiency, and cost-effectiveness. Batteries undergo continuous price and discharge cycles, and their degradation over the years without delay affects the overall performance of the standard machine. This study applies machine learning techniques, specifically the Random Forest algorithm, to predict the final useful lives (RUL) of rechargeable batteries. Operational parameters such as state of charge (SOC), voltage, current, temperature, and cycle count number are utilized as enter features for version education. The Random Forest version is trained and tested the use of a dataset that reflects various operating and fault situations, enabling the algorithm to capture complex nonlinear relationships between battery behavior and degradation patterns. The predictive model provides accurate estimations of battery health and expected lifetime, offering a valuable tool for proactive maintenance planning and early replacement strategies. By implementing such a data-driven approach, battery management systems can move beyond traditional threshold-based monitoring to intelligent, predictive diagnostics. This contributes to improving system reliability, reducing downtime, and extending the overall lifecycle of electric vehicles and energy storage applications.
Optimized Hybrid Insulating Oils for Advanced Transformer T. Barathkumar, R. Lal Raja Singh, M. Shalini, R. Vineth, M. Muneeswaran 13th International Conference on Intelligent Embedded Microelectronics Communication and Optical Networks Iemecon 2025, 2025 The growing demand for sustainable and excessive-performance insulating beverages in strength transformers has pushed widespread research into alternatives to traditional mineral oil. This evaluate synthesizes findings from latest studies on mineral oils, natural esters, blended formulations, and nanofluids to evaluate their electro-thermal-physical traits, dielectric behavior, chemical balance, and environmental impact. Natural esters which include coconut, palm, and different vegetable oils have received attention because of their biodegradability and favorable thermal homes, while mixed mineral-ester oils provide a balance among cost, balance, and environmental overall performance. The incorporation of nanoparticles, which includes <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\text{TiO}_{2}, \text{ZnO}$</tex>, and ferrite substances, has proven excellent improvements in breakdown voltage, thermal conductivity, and oxidative resistance. Optimization methods along with Taguchi-based grey relational evaluation and AI-superior statistical evaluation have supplied new insights into overall performance enhancement strategies. However, challenges stay regarding long-time period stability, compatibility with stable insulation, and large-scale implementation expenses. This paper categorizes and compares over thirty latest works, highlighting tendencies in additive-based totally property enhancement, ageing performance beneath thermal strain, and emerging green dielectric formulations. The evaluate in addition identifies studies gaps which includes the need for standardized checking out protocols, advanced modeling of deterioration mechanisms, and deeper investigation into hybrid nanofluids. By consolidating current improvements, this painting's objective to aid destiny innovations in transformer liquid insulation, bridging performance requirements with sustainability desires within the evolving power sector.
Opti Grid: AI-Based Energy Management System for Solar-Powered Microgrids P.Fathima Sapna, Lal Raja Singh R 2024 2nd World Conference on Communication and Computing Wconf 2024, 2024 As electricity demand continues to rise, electrical engineers will turn to renewable-based energy sources like solar panels and their batteries to meet this demand efficiently. By integrating renewable energy with artificial intelligence, the aim is to create a more sustainable and eco-friendly solution. The main focus is on developing an energy-management system for solar-powered microgrids by using a modified firefly optimizer approach. This system will optimize the dispatch of energy resources in grid-connected systems by efficiently utilizing solar photovoltaic technology and energy storage systems. The proposed system will validate its performance under varying weather conditions, which include sunny and cloudy days, to account for the stochastic nature of solar energy. The Opti Grid system will represent a step towards achieving a more efficient and sustainable smart grid environment. This will reduce greenhouse gas emissions while meeting the increasing electricity demand.
Design and Development of Smart System for the Identification and Diversion of Wild Animal in Agricultural Field R. Lal Raja Singh, V. Thirumalaivasan, N. Navin Kumar, R. Adharsh 10th International Conference on Advanced Computing and Communication Systems Icaccs 2024, 2024 As human populations continue to expand, conflicts between agriculture and wildlife have become increasingly prevalent. The “Design and Development of a Smart System for the Identification and Diversion of Wild Animals in Agricultural Field” addresses this critical issue by proposing an innovative solution that leverages cutting-edge technology to minimize crop damage and protect both agricultural livelihoods and wildlife populations. This project centers on the creation of a comprehensive smart system that integrates various sensors, including cameras, infrared detectors, and machine learning algorithms, to accurately identify and track wild animals entering agricultural fields both Day-time and Night-time. By using 360 degree night vision camera, samples are taken continuously. With the samples, Raspberry pi compare it with the database to detect the animal By which it could be activate the irritating frequency or high beam for certain wild animal. Because of using raspberry Pi the image processing and processing speed will be high. Upon detection, the system employs real-time data analysis to categorize the species and assess the potential threat to crops. Subsequently, it triggers a non-harmful diversion mechanism, such as flashing lights, sounds, or automated barriers, to deter the animals from causing damage. The objectives of this project include reducing crop losses, mitigating Conflicts between people and wildlife, as well as encouraging agriculture and wildlife coexistence. Moreover, it aims to provide valuable data for conservation efforts and wildlife monitoring. By implementing this Smart System, we anticipate not only safeguarding agricultural yields but also contributing to the conservation of wildlife populations. The research and technology behind this project have the potential to serve as a model for sustainable cohabitation between humans and the world.
Design and Development of Air Bag Assisted Pneumatic Borewell Rescue System R. Lal Raja Singh, R. Selvamathi, G. Gokul, P. Infant Praveen Jose Icdcs 2024 2024 7th International Conference on Devices Circuits and Systems, 2024 Operations to rescue people from borewells are difficult since they are deep and tight and frequently include rescuing people who are stuck, particularly kids. Compact and portable, the robot is made to be carried to the rescue location with ease. For movement in the uneven and constricted borewell environment, the robot is equipped with wheeled or tracked locomotion systems. Proficiencyin remote control of the robot enables skilled operators to make accurate movements and judgments by utilizing real-time data. Seventy percent of rescue missions fail due to this convoluted method. With the ability to save lives and lower hazards to rescue workers, it provides an essential tool for rescue teams to react swiftly and efficiently to situations involving people stuck in borewells. Operations for rescue in borewells. Creating a safe and effective method of rescuing people, including children, who are confined to borewells is the goal of the design and development of a robotic device for borewell rescue operations. The robot should have sensors to identify the victim and determine their status, and it should be able to maneuver through the uneven and small borewell shaft. Lifting the victim to safety should also be possible for the robot. By utilizing a combination of pneumatic and air bag technologies, our method seeks to address these problems by drastically cutting down on rescue time and improving process safety.
Charging infrastructure facilitate a large-scale Introduction of electric vehicle in urban areas using hybrid technique: A RBFNN-SPOA approach J. Chitra, R. Lal Raja Singh, R. Leena Rose Energy and Environment, 2023 A hybrid technique is proposed for the effects of different roll-out techniques for charging the infrastructure that enables large-scale introduction of electric vehicles (EVs). The proposed hybrid technique is the combined execution of both Radial Basis Function Neural Network (RBFNN) and Student psychology optimization algorithm (SPOA), together called as RBFNN-SPOA strategy. The proposed method contains 3 kinds of agents operate in the environment from which charging stations is located. The communication among these agents are simulated in 3 ways. They are (1) charging process from which the EV driver cooperates with available charging stations and other electric vehicle drivers, (2) the process of purchasing a vehicle of non-electric vehicle car owners from which they take current charging infrastructure utilization into account, (3) the installment process of new charging stations through charging point operator (CPO) is based on placement tactic depends on charging station (CS) utilization. Firstly, a larger dataset on real charging patterns are utilized to design the charging behaviour of agents by RBFNN. Secondly, the proposed approach contains significantly more communication among electric vehicle drivers compared to existing approaches and also more precisely specifies the difficult system of on-street electric vehicle charging at an urban context. Thirdly, the relation among charging infrastructure and electric vehicle adoption based on experimental choice, while the existing methods provides assumptions by using SPOA. Finally, the proposed approach is implemented in MATLAB or Simulink platform and its performance is compared with existing approaches.
Optimal planning and allocation of Plug-in Hybrid Electric Vehicles charging stations using a novel hybrid optimization technique Ayyappan Subramaniam, Lal Raja Singh Ravi Singh Plos One, 2023 India’s expanding population has necessitated the development of alternate transportation methods with electric vehicles (EVs) being the most indigenous and need for the current scenario. The major hindrance is the undue influence on the power distribution system caused by incorrect charging station setup. Renewable Energy Sources (RES) have a lower environmental impact than the non-renewable sources of energy and due to which Plug-in Hybrid Electric Vehicles (PHEV) charging stations are installed in the highest-ranking buses to facilitate their effective placements. Based on meta-heuristic optimization, this study offers an effective PHEV charging stations allocation approach for RES applications. The primary objective of the developed system is to create a charging network at a reasonable cost while maintaining the operational features of the distribution network. These troublesare handled by applying meta-heuristic algorithms and optimum planning based on renewable energy systems to satisfy the outcomes of the variables. As a result, by adding charging station parameters, this research proposes to conceptualize the distribution of optimal charging stationsas multiple-objectives of the problem. Furthermore, the PHEV RES and charging station location problem is handled in this study by deploying a novel hybrid algorithm termed as Atom Search Woven Aquila Optimization Algorithm (AT-AQ) that includes the ideas of both Aquila Optimizer (AO) and Atom Search Optimization (ASO) Algorithms. In reality, Aquila Optimizer is a unique population-based optimization approach energized by Aquila’s behaviour when seeking prey and it solves the problems of slow convergence and local optimum trapping. According to the findings of the experiments, the proposed model outperformed the other methods in terms of minimized cost function.
Comparision of hybrid intelligent techniques to solve unit commitment problem with cooling-banking constraints International Journal of Applied Engineering Research, 2015
An efficient and improved artificial neural network algorithm to solve unit commitment problem with cooling banking constraints European Journal of Scientific Research, 2011
A Hybrid Particle Swarm Optimization employing Genetic Algorithm for unit commitment problem International Review of Electrical Engineering, 2011
RECENT SCHOLAR PUBLICATIONS
A Triband Graphene-Based Linear Array THz Antenna for 6 G IoT Applications Using Spotted Hyena Optimizer KN Sreekumar, G Ranganathan, RLR Singh, V Bindhu Optik, 172510 , 2025 2025 Citations: 2
Arduino Controlled Smart Battery Management System Integrated with Cloud for Realtime Monitoring RLR Singh, YK Devanandhan, A Ravivarma 2025 6th International Conference on Inventive Research in Computing … , 2025 2025
IOT based energy management in smart grid under price based demand response based on hybrid FHO-RERNN approach C Balasubramanian, RLR Singh Applied Energy 361, 122851 , 2024 2024 Citations: 47
Design and Development of Air Bag Assisted Pneumatic Borewell Rescue System RLR Singh, R Selvamathi, G Gokul, PIP Jose 2024 7th International Conference on Devices, Circuits and Systems (ICDCS … , 2024 2024 Citations: 4
Design and Development of Smart System for the Identification and Diversion of Wild Animal in Agricultural Field RLR Singh, V Thirumalaivasan, NN Kumar, R Adharsh 2024 10th International Conference on Advanced Computing and Communication … , 2024 2024 Citations: 1
IoT Based Energy Management System in Smart Grid C Balasubramanian, RLR Singh 2023 Innovations in Power and Advanced Computing Technologies (i-PACT), 1-6 , 2023 2023 Citations: 8
Charging infrastructure facilitate a large-scale Introduction of electric vehicle in urban areas using hybrid technique: A RBFNN-SPOA approach J Chitra, R Lal Raja Singh, R Leena Rose Energy & Environment 34 (8), 3103-3129 , 2023 2023 Citations: 3
Integrated Perturb and Observe Algorithm to Extract Maximum Power in Hybrid Renewable Energy System RLR Singh, S Agathiyan, GG Subramanian, K Pradheep 2023 First International Conference on Advances in Electrical, Electronics … , 2023 2023
Design and Development of Low Power and Area Efficient Design for VLSI Circuits V Kamalkumar, RLR Singh 2023 4th International Conference on Smart Electronics and Communication … , 2023 2023 Citations: 1
Optimal planning and allocation of Plug-in Hybrid Electric Vehicles charging stations using a novel hybrid optimization technique A Subramaniam, LRS Ravi Singh Plos one 18 (7), e0284421 , 2023 2023 Citations: 19
High-performance fuzzy optimized deep convolutional neural network model for big data classification based on the social internet of things B Shaji, RLR Singh, KL Nisha The Journal of Supercomputing 79 (9), 9509-9537 , 2023 2023 Citations: 8
Power Quality Enhancement of the Distribution Network by Multilevel STATCOM B Arthi, R Thamizharasan, MP Mohandass, RLR Singh 2023 Second International Conference on Electronics and Renewable Systems … , 2023 2023 Citations: 1
Design and Fabrication of Solar Powered Air Quality Monitoring System RLR Singh, K Arulselvan, A Indhumathi, S Iswarya, G Namitha 2023 Second International Conference on Electronics and Renewable Systems … , 2023 2023 Citations: 2
AI Enabled Smart Campus for Health Safety and Monitoring RLR Singh, V Bhuvaneswari, J Ebinesh, K Stalinraj 2023 Second International Conference on Electronics and Renewable Systems … , 2023 2023
Optimum Transistor Sizing of CMOS Differential Amplifier Using Tunicate Swarm Algorithm V Kamalkumar, R Lal Raja Singh Journal of Circuits, Systems and Computers 32 (03), 2350051 , 2023 2023 Citations: 10
Electrical Load Forecasting Techniques & Methods: An Overview PF Sapna, RLR Singh International Journal of Advances in Engineering and Emerging Technology 13 … , 2022 2022 Citations: 2
A novel deep neural network based marine predator model for effective classification of big data from social Internet of Things B Shaji, R Lal Raja Singh, KL Nisha Concurrency and Computation: Practice and Experience 34 (25), e7244 , 2022 2022 Citations: 4
Optimal design of proportional integral derivative acceleration controller for higher‐order nonlinear time delay system using m‐MBOA technique J Arulvadivu, S Manoharan, R Lal Raja Singh, S Giriprasad International Journal of Numerical Modelling: Electronic Networks, Devices … , 2022 2022 Citations: 16
ANFIS-BCMO technique for energy management and consumption of energy forecasting in smart grid with internet of things C Balasubramanian, R Lal Raja Singh Journal of Intelligent & Fuzzy Systems 43 (6), 7577-7593 , 2022 2022 Citations: 9
High-Frequency Resonance Analysis and Stabilization Control Strategy of Modular Multilevel Converter Based on Eigenvalue Method LRS SathishKumarS Annals of the Romanian Society for Cell Biology, 15623-15630 , 2021 2021
MOST CITED SCHOLAR PUBLICATIONS
IOT based energy management in smart grid under price based demand response based on hybrid FHO-RERNN approach C Balasubramanian, RLR Singh Applied Energy 361, 122851 , 2024 2024 Citations: 47
Optimal planning and allocation of Plug-in Hybrid Electric Vehicles charging stations using a novel hybrid optimization technique A Subramaniam, LRS Ravi Singh Plos one 18 (7), e0284421 , 2023 2023 Citations: 19
Optimal design of proportional integral derivative acceleration controller for higher‐order nonlinear time delay system using m‐MBOA technique J Arulvadivu, S Manoharan, R Lal Raja Singh, S Giriprasad International Journal of Numerical Modelling: Electronic Networks, Devices … , 2022 2022 Citations: 16
Optimum Transistor Sizing of CMOS Differential Amplifier Using Tunicate Swarm Algorithm V Kamalkumar, R Lal Raja Singh Journal of Circuits, Systems and Computers 32 (03), 2350051 , 2023 2023 Citations: 10
ANFIS-BCMO technique for energy management and consumption of energy forecasting in smart grid with internet of things C Balasubramanian, R Lal Raja Singh Journal of Intelligent & Fuzzy Systems 43 (6), 7577-7593 , 2022 2022 Citations: 9
A hybrid approach based on PSO and EP for proficient solving of Unit Commitment Problem RLR Singh, CCA Rajan International Conference and Utility Exhibition on Power and Energy Systems … , 2011 2011 Citations: 9
IoT Based Energy Management System in Smart Grid C Balasubramanian, RLR Singh 2023 Innovations in Power and Advanced Computing Technologies (i-PACT), 1-6 , 2023 2023 Citations: 8
High-performance fuzzy optimized deep convolutional neural network model for big data classification based on the social internet of things B Shaji, RLR Singh, KL Nisha The Journal of Supercomputing 79 (9), 9509-9537 , 2023 2023 Citations: 8
Economic emission dispatch of hydro-thermal-wind using CMQLSPSN technique LRRLRSR Singh IET Renewable Power Generation 14 (Issue 14), 2680 – 2692 , 2020 2020 Citations: 8
Development of Hybrid Algorithm Based on PSO and NN to Solve Economic Emission Dispatch Problem DRLRS Leena Rose R, Dr. B Dora Arul Selvi Circuits and Systems 7 (7), 2323-2331 , 2016 2016 Citations: 7
Automatic and real time classification of power quality disturbance using statistical moments SE Jose, RLR Singh, R Rajagopal AIP Conference Proceedings 2327 (1), 020050 , 2021 2021 Citations: 6
A Hybrid Particle Swarm Optimization Employing Genetic Algorithm for Unit Commitment Problem CCAR Lal Raja Singh.R International Review of Electrical Engineering 6 (7), 3211-3217 , 2011 2011 Citations: 5
Design and Development of Air Bag Assisted Pneumatic Borewell Rescue System RLR Singh, R Selvamathi, G Gokul, PIP Jose 2024 7th International Conference on Devices, Circuits and Systems (ICDCS … , 2024 2024 Citations: 4
A novel deep neural network based marine predator model for effective classification of big data from social Internet of Things B Shaji, R Lal Raja Singh, KL Nisha Concurrency and Computation: Practice and Experience 34 (25), e7244 , 2022 2022 Citations: 4
A Novel Energy Management System using Renewable Distribution Generation Units AO Deepa, RLR Singh, RL Rose JEES 2, 1-11 , 2016 2016 Citations: 4
Charging infrastructure facilitate a large-scale Introduction of electric vehicle in urban areas using hybrid technique: A RBFNN-SPOA approach J Chitra, R Lal Raja Singh, R Leena Rose Energy & Environment 34 (8), 3103-3129 , 2023 2023 Citations: 3
Smart Agriculture using IoT for Plant Pathology and Task Automation RLR Singh, R Thamizharasan, MP Mohandass, E Udayakumar 2021 7th International Conference on Advanced Computing and Communication … , 2021 2021 Citations: 3
Voltage Control of a STATCOM using Posicast and P+Resonant Controller at a Fixed Speed Induction Generator Wind Farm JC R Lal Raja Singh, R Leena Rose Journal of Electrical Engineering and Science 2 (2), 12-23 , 2016 2016 Citations: 3
A Triband Graphene-Based Linear Array THz Antenna for 6 G IoT Applications Using Spotted Hyena Optimizer KN Sreekumar, G Ranganathan, RLR Singh, V Bindhu Optik, 172510 , 2025 2025 Citations: 2
Design and Fabrication of Solar Powered Air Quality Monitoring System RLR Singh, K Arulselvan, A Indhumathi, S Iswarya, G Namitha 2023 Second International Conference on Electronics and Renewable Systems … , 2023 2023 Citations: 2
