Mrs. Pushpalatha received her B.E ., Degree in Electrical and Electronics Engineering from Annai Mathammal Sheela Engineering College, Namakkal, Tamilnadu and M.E., degree in Power Electronics and Drives from Karpagam University, Tamilnadu. Currently she is working as Assistant Professor (Selection Grade) in the Department of Electrical and Electronics Engineering at Sri Eshwar College of Engineering, Coimbatore. Her current research interests are Power Electronics and Drives, Power Quality, Internet of Things, Electric Vehicles and Artificial Intelligence. She is life member of the Indian Society for Technical Education (ISTE). She has guided many student projects in the area of IoT and Power Electronics. She has a total of 12.3 years of experience teaching engineering.
EDUCATION
B.E.-EEE, M.E. - Power Electronics and Drives, (
RESEARCH INTERESTS
Power Electronics, Power Systems, Electrical Machines, Renewable Energy
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Scopus Publications
Scopus Publications
SmartRide: the next-gen bus system Hemananth B., Pushpalatha N., Akalya D., Jaishree S., Mathimalar C., Sandhiya N. Proceedings of SPIE the International Society for Optical Engineering, 2026
Cyber Threat Detection in 6G Internet of Things Using Deep Learning and Privacy Preservation via Blockchain C. Nandagopal, R. Rajesh Kanna, K. Sangeetha, Pushpalatha Naveenkumar International Journal of Communication Systems, 2026 The quick propagation of Internet of Things (IoT) devices in 6th Generation (6G) networks intensifies security challenges due to high‐dimensional and diverse nature of IoT data, which complicates feature selection and increases computational overhead. Dynamic and evolving attack patterns, including various intrusion types, malware, denial‐of‐service attempts, and coordinated botnet attacks, further reduce detection reliability. To address these challenges, Optimized Periodic Implicit Generative Adversarial networks with advanced Transformer (OPIGAT) proposes an end‐to‐end framework for robust and scalable IoT security. The framework begins with a preprocessing stage that handles missing values, outliers, and normalization for clean and consistent data. Feature optimization occurs through a Hybrid Tuna Particle Swarm Optimization Algorithm (HTPSO), which Merges Particle Swarm Optimization (PSO) global search capability with Tuna Swarm Optimization (TSO) spiral foraging‐inspired local refinement, enabling precise selection of compact and highly discriminative features while reducing dimensionality. OPIGAT classifier detects diverse attacks, with the generative component synthesizing realistic traffic patterns and the transformer module capturing contextual relationships, enhancing anomaly detection and reducing false positives. Finally, a lightweight blockchain integrated with InterPlanetary File System (IPFS) ensures secure and scalable data management, employing proof of authority, Elliptic Curve Cryptography (ECC) with Ring signature encryption, and smart contract–based revocation to maintain privacy, integrity, and efficiency. Extensive experiments on CICIoT‐2023 and ROUT‐4‐2023 datasets demonstrate superior accuracy (98.78% and 97%), high detection efficiency (98.21%), and a low false alarm rate (20%), while IPFS‐enabled storage supports seamless scalability. These results establish OPIGAT as a secure, efficient, and highly effective solution for 6G IoT intrusion detection.
A Farmer Friendly AI Powered Smart Agriculture Loan Appraisal System by Considering Their Land Yield Capacity N. Pushpalatha, Nandhini, G. M. Santhiya, Firoz Khan, Ahmad Alkhayyat Lecture Notes in Electrical Engineering, 2026 Agriculture is an important industry that facilitates economic development, employment, and food security. But financial constraints frequently hinder farmers from embracing advanced farming methods, which results in decreased productivity. Farm loans are an important source of finance that helps farmers to invest in improved machinery, quality seeds, fertilizers, and efficient irrigation systems. This proposed method analyzes the various agricultural loan schemes, their contribution to increasing farming productivity, and the difficulties farmers encounter in obtaining financial support. The research also investigates various loan schemes, comparing government-guaranteed loans, private sector lending, and online lending platforms. Through a review of current literature and research methods, this paper identifies the performance of different loan models and proposes recommendations for improved accessibility and efficiency in farm financing. The results highlight the necessity of policy changes, financial education initiatives, and the inclusion of digital banking technologies for improving access to loans and enhancing repayment systems to ensure sustainable farm development.
Track Sential N. Pushpalatha, R. Vidyalakshmi, A. Pradeepa, M. Maheshwaran, K. Sabareeshwaran, V. Gomathi Lecture Notes of the Institute for Computer Sciences Social Informatics and Telecommunications Engineering Lnicst, 2026
An Effective Content Based Image Retrieval Using Multi Feature Fusion Algorithm with Optimized Retrieval Technique of Soft Computing Approach Pushpalatha N, Sumendra Yogarayan, Selvi A, Gunapriya D, Siti Fatimah Abdul Razak Journal of Machine and Computing, 2025 With the increasing digitization of healthcare, hospitals generate and store thousands of medical images daily, creating large-scale datasets that demand efficient retrieval solutions. Content-Based Image Retrieval (CBIR) systems address this by identifying relevant images based on visual features rather than textual metadata. While various CBIR approaches exist, many suffer from low precision, redundant retrievals, and slow query processing times. This paper introduces a novel hybrid CBIR framework that significantly improves retrieval accuracy and efficiency by integrating Principal Component Analysis (PCA) for texture extraction, Wavelet Transform (WT) for shape feature extraction, and Canonical Correlation Analysis (CCA) for advanced feature fusion. Unlike previous methods that rely on single-feature analysis or basic fusion strategies, our approach combines multiple complementary features into a unified representation, enhancing the system's ability to discern subtle patterns in medical images. CCA helps to find features from the medical images that are maximally related, e.g., the part of the breast that usually co-occur when someone is under observation. Additionally, we apply a customized classification strategy using Fuzzy Support Vector Machine optimized with Modified Whale Optimization Algorithm (FSVM-MWOA), which enhances model adaptability and retrieval precision. FSVM a variant of SVM that incorporates fuzzy logic to handle uncertainty and noisy data, MWOA an enhanced version of the bio-inspired Whale Optimization Algorithm, used here to optimize the parameters of the FSVM. Experimental results show that the proposed system achieves over 90% retrieval accuracy, reduces query response time by up to 40%, and minimizes redundancy, outperforming conventional CBIR techniques. This integrated approach not only addresses the limitations of existing methods but also introduces a scalable and robust solution tailored to the specific challenges of medical image datasets.
OPTIMIZED PHOTOVOLTAIC-DYNAMIC VOLTAGE RESTORER (PV-DVR) SYSTEM FOR POWER QUALITY ADVANCEMENT IN GRID Venkatesh Kumar Pandiyan, Aravinda Kothiyar, Pushpalatha Naveenkumar, Manikandan Chidambara Sekar Environmental Engineering and Management Journal, 2025 The increasing penetration of power electronics in modern electrical systems has introduced significant power quality (PQ) issues, notably voltage sags, swells, flickers, and harmonics.These disturbances not only threaten grid stability but also result in energy inefficiencies and increased environmental burdens due to system losses.To address these challenges sustainably, this study presents an optimized Dynamic Voltage Restorer (DVR) topology powered by a photovoltaic (PV) system, offering a dual benefit: effective PQ enhancement and integration of clean, renewable energy.The proposed DVR employs a seven-level inverter with a reduced switch count to minimize component usage and switching losses.A Proportional-Integral (PI) controller is used for realtime regulation, and the system's response is evaluated under multiple fault conditions through MATLAB simulations.Results confirm superior voltage sag compensation, harmonic suppression, and power efficiency.The integration of PV not only reduces dependence on conventional grid sources but also contributes to a greener energy infrastructure, aligning power quality solutions with environmental sustainability goals.
AI in Mechatronics Engineering Pushpalatha Naveenkumar, Vandana Sharma, Devarajan Gunapriya Handbook of AI Based Mechatronics Systems and Smart Solutions in Industrial Automation, 2025 Robotic engineering, with a focus on the combination of artificial intelligence (AI) together with robotics, computers, electronics, and mechanical systems, as well as control system implementations, allows for many inventions. Key applications of AI in mechatronics engineering practice will be advanced production, intelligent robotics, predictive maintenance, and design optimization control. Robotics engineers are able to incorporate AI into their systems such that data can be collected, analyzed, and modeled, then used to enhance the dependability, flexibility, as well as performance of the systems. This chapter researches the engineering integration of AI along with mechatronics and the industries it is disrupting. Moreover, it addresses the basic definition of AI and its main application areas within mechatronics and its prospects toward enabling enhanced control systems, predictive maintenance, design optimization, intelligent robotics, and improved production in any contemporary industry. Such systems may be developed by mechatronics engineers due to the enriched capabilities of AI in data analysis, recognition, and decision-making. This study also addresses the limits and moral issues to the ethics of combining artificial and human power and suggests ideal steps for more study and advancement in the areas outlined.
Applications of Hyperautomation in Finance and Banking Industries S. Arunarani, A. Prasanth, N. Pushpalatha, Mariya Ouaissa Hyperautomation for Next Generation Industries, 2025 One of the most important aspects of digitalization will be digital process automation, often known as “Hyperautomation,” a term popularized by Gartner. The process of automating end-to-end company operations to relieve the stress on human workers, maximize efficiencies, and cut costs is known as hyperautomation. It is a deep level of digital autonomy. Automation has a substantial impact on the banking and financial sectors, respectively. Hyperautomation boosts effectiveness and productivity, lowers costs, and opens up new prospects in the banking and financial sector. A higher standard of customer service is also being provided thanks to it. One of the first sectors to use this technology extensively was the financial sector. In addition to automating some back-office tasks like risk management and credit scoring, banks use it to process payments, manage accounts, and process payments. everything from contact-free transactions to QR scanning and several financial firms have come to understand the actual potential of hyperautomation thanks to the use of robotic process automation (RPA) in the insurance business. Hyper-function automation is to speed up how quickly banks can handle transactions, manage their assets, and offer customers goods and services. Additionally, it assists them in achieving their objectives by enhancing the accuracy and transparency of the processes they must carry out. Use cases for various hyperautomation technologies in banking and finance, including chatbots, robotic process automation (RPA), intelligent automation, and robotic intelligence (AI). Hyperautomation can provide end-to-end process automation by combining these technologies. Hyperautomation is being used by more businesses in the banking, financial services, and insurance (BFSI) industry to reinvent their processes and improve efficiency, profitability, speed, and accuracy.
AI Frameworks in Mechatronics Engineering Gunapriya Devarajan, Pushpalatha Naveenkumar, Malathy Batumalay, Vinoth Kumar Handbook of AI Based Mechatronics Systems and Smart Solutions in Industrial Automation, 2025 Artificial intelligence (AI) frameworks have become essential tools in the evolution of mechatronics engineering, enabling the transition from traditional systems to intelligent, adaptive, and efficient solutions. Mechatronics, as a multidisciplinary field, integrates mechanical, electrical, and computer engineering. By incorporating AI, these systems can perform tasks with human-like capabilities, such as perceiving, analyzing, learning, and making decisions, transforming the way machines interact with their environment and execute tasks. The integration of AI into mechatronics offers numerous advantages. It automates repetitive and hazardous tasks, allowing human resources to focus on more complex and creative endeavors. AI-driven systems improve accuracy, precision, and adaptability while analyzing vast data volumes to make informed decisions. These systems also optimize energy consumption, reduce production time, minimize workplace risks, and lower operational and maintenance costs. Additionally, AI fosters seamless human–machine collaboration, making it a cornerstone of modern mechatronic applications. AI frameworks provide the software tools and libraries needed to implement intelligent systems in various domains. Popular frameworks like TensorFlow, PyTorch, Robot Operating System (ROS), and Scikit-learn empower engineers to design and deploy AI-driven mechatronic systems. These frameworks have applications in diverse sectors, including industrial automation, healthcare, and business, where they enable automation, enhance quality control, streamline processes, and improve decision-making. By leveraging these frameworks, mechatronics has experienced a significant transformation, paving the way for intelligent, efficient, and adaptable systems that redefine the possibilities of modern engineering.
Extendable AI in Mechatronics Engineering Pushpalatha Naveenkumar, Surendar Rangaraju, T. Kokilavani, K. Kannan, M Praveen Kumar Handbook of AI Based Mechatronics Systems and Smart Solutions in Industrial Automation, 2025 Indeed, the use of artificial intelligence (AI) in mechanical engineering and mechatronics has recently started to pick up pace as there is increased advancement in technology. That is why as systems become more complex or in fact more automated, the need for extensible AI is rising. These systems are capable of learning and therefore engineers are capable of developing solutions which can change with the ever-changing needs and be more efficient. Beyond that, the fact that such systems may also exhibit a human-like behavior should be taken into consideration when designing the systems in the future generations of robots, cars, and healthcare ventures. Thus, it is made clear that AI is fundamental in the integration of mechanical engineering and mechatronics, and also due to extensiveness that AI has introduced, more new innovative inventions generated positively in the field can be explored.
SUSTAINABLE ENERGY AND POWER QUALITY ASSESSMENT BY INVASIVE THERMOGRAPHY AND ENERGY AUDIT IN THE TEA INDUSTRY: A SCIENTIFIC STUDY Journal of Environmental Protection and Ecology, 2024
Hydrolink-Automatic Water Level Controller N. Pushpalatha, T. Cheran, V. Ramya, S. Selvanayakam, V. Yamunaa 2nd International Conference on Intelligent Data Communication Technologies and Internet of Things Idciot 2024, 2024
Field Monitoring and Automatic Agricultural System Maheshwaran M, D Gunapriya, Govindaraj V, B.Padmini Devi, Pushpalatha N, N. Abinaya Proceedings of 2024 International Conference on Science Technology Engineering and Management Icstem 2024, 2024
Machine Learning–Based Pre-Stroke Detection System Maheshwaran M, Kiruthiga Devi V, D Gunapriya, Pushpalatha N, S. Sam Karthik, Selvi A Proceedings of 2024 International Conference on Science Technology Engineering and Management Icstem 2024, 2024
Detection of Mishap and Myocardial Infraction Pusphalatha N, Sri Dhananjayan K, Senthooriya O S, Tharunprasath K, J.Arulvadivu, Gowtham M 2024 International Conference on Recent Innovation in Smart and Sustainable Technology Icrisst 2024, 2024
SIMULATION ANALYSIS OF A MULTILEVEL INVERTER IN A GRID-CONNECTED HYBRID RENEWABLE SYSTEM FOR SUSTAINABLE DEVELOPMENT Journal of Environmental Protection and Ecology, 2023
AI-BASED POWER QUALITY IMPROVEMENT OF A UPS FOR A SUSTAINABLE ELECTRICAL NETWORK Journal of Environmental Protection and Ecology, 2023
A Review on Intelligent Water Bottle Powered by IoT Pushpalatha N, Nohit Venakata Seetha Sai Balaji, Guru Vishnu Varthan, R Sivakumar, Linda Cecilia Tracy Maule, D Naveenkumar 2023 9th International Conference on Advanced Computing and Communication Systems Icaccs 2023, 2023
A General Investigation of Battery Handling Techniques Driven by IoT D. Gunapriya, N. Pusphalatha, S. Sudharsan, S. Pandi, R. SivaKumar, P. Vinoth Kumar Proceedings of the 4th IEEE International Conference on Smart Technologies in Computing Electrical and Electronics Icstcee 2023, 2023
Review and Comparison on Types of Solar Tracking using PNT Systems W. Rajan Babu, N. Pushpalatha, L. Catherine, K. Janani, Sandip S Kanase, Prathamesh Patil Proceedings of the 7th International Conference on Intelligent Computing and Control Systems Iciccs 2023, 2023
Gesture-based Control of a Bionic Arm - A Prototype Design N. Pushpalatha, Sheikameer Batcha, V. Yesvanthkrishna, S. Rathinamala, B. Padmini Devi, Gomarhi V Proceedings 7th International Conference on Computing Methodologies and Communication Iccmc 2023, 2023
Arduino Based Smart Vacuum Cleaner Pusphalatha N, C. Mohanraj, Karthikraja S, Rameela K, Akalya A, Pavadarani S P 2023 10th IEEE Uttar Pradesh Section International Conference on Electrical Electronics and Computer Engineering Upcon 2023, 2023
Conspiracy in the Stealing of Electricity Detection Through the IOT C. Mohanraj, N. Pushpalatha, Muthumanidevi B, Amirtha Varsheni S, R. Sivakumar, Vandana Sharma, Ahmed Alkhayyat Proceedings of 2023 3rd International Conference on Innovative Practices in Technology and Management Iciptm 2023, 2023
An Exhaustive Investigation of Battery Management System (BMS) D. Gunapriya, N. Pusphalatha, S. Sudharsan, S. Pandi, L. Catherine, Vandana Sharma, Ahmed Alkhayyat Proceedings of 2023 3rd International Conference on Innovative Practices in Technology and Management Iciptm 2023, 2023
CARE CANE-Versatile Supportive Cane for Vision-Impaired B. Hemananth, N. Pushpalatha, V. Aravind Kumar, N. Karthick Prabhu, V. Yogaraj, A. Yuvaraj 8th International Conference on Smart Structures and Systems Icsss 2022, 2022
Automated Agronomic Bot for Green Ailment Scanner S.Venkatesa Prasath, N. Pushpalatha, D. Gunapriya, P.Mukesh Kumar, R.T. Santhosh, S. Srinivasan Proceedings of 5th International Conference on Contemporary Computing and Informatics Ic3i 2022, 2022
