Electrical and Electronic Engineering, Control and Systems Engineering, Engineering, General Engineering
10
Scopus Publications
5
Scholar Citations
1
Scholar h-index
Scopus Publications
Examination of the recent research trends on controllers in the AI powered UAV B. Swapna, A. Lavanya, G. Kavitha, M. Sujitha, C. Anuradha, S. Vijayalakshmi, K. Jeevitha, R. Kasthuri, M. Kamalahasan Humans and Generative AI Tools for Collaborative Intelligence, 2025 The development of AI is based on research into the patterns and processes of human thought. Improved software and systems are developed as a direct outcome of these research initiatives. Deep learning (DL), a subfield of AI, allows computers to robotically acquire new abilities by analysing training sets, which are collections of previously received data. The AI technique known as deep reinforcement learning is very useful for autonomous UAVs. The fundamental characteristics of autonomous driving, particularly talks and human conversations, including making choices, make robotic motor vehicles the perfect fit for reinforcement learning. This paper presents a new viewpoint by exploring the AI features realized in current journals. This article aims to realize the attitude control is so important for UAVs and moreover AI controller is better than a conventional one. This article explores the abundant AI technologies that may be utilized for attitude control, path planning and obstacle avoidance of UAVs with many applications. Illustrates the way AI in UAV systems on an everyday basis.
Optimistic machine learning algorithm to identify producer and consumer risks in the medical field using double sampling plan B. Swapna, D. Manjula, G. Uma, G. Kavitha, D. SenthilKumar, M. Sujitha, K. Jeevitha, A. Lavanya Convergence of Internet of Medical Things Iomt and Generative AI, 2025 The specific form of statistical quality control, applied to the medical field to ensure product excellence and patient safety. Specifically, the proposed method employs a Machine Learning Algorithm (MLA) to assist in decision-making about accepting or rejecting inspected medical samples. The algorithm is trained using data from double sampling plan tables, enabling it to generate closed-form solutions for sample size while accounting for producer and consumer risks. This automation ensures precision in interpreting double sampling plan tables without compromising quality. provides flexibility for medical quality controllers, allowing for the consideration of specific requirements while minimizing time and cost during inspections. It addresses producer and consumer risks at predefined levels, while also incorporating other key quality parameters. With this system, medical professionals can estimate sample size at fixed producer and consumer risk levels, or predict these risks at a given sample size, ensuring comprehensive risk management and quality assurance in medical products.
A Robust Methodology Design for Removing Noise Content in Blurred and Deblurred Images Using Neural Optimization Principle M. Sujitha, S U Prabha, G. Dhanalakshmi, Iyswariya A, Vunnava Dinesh Babu, Nakka Nagaraju Proceedings Iceconf 2025 2025 2nd International Conference on Artificial Intelligence and Knowledge Discovery in Concurrent Engineering, 2025 Image degradation in the form of blur and noise remains a significant challenge in computer vision, affecting critical applications such as surveillance, medical imaging, and photography. The classical approaches treat the problems of denoising or deblurring separately, thus achieving a suboptimal result in case of the presence of both problems. Here, we present a Hybrid Deblurring-Denoising Model that is based on Neural Optimization and addresses both issues on a single model. The method presents the process of blurred and noisy image degradation as a constrained optimization problem, in which the neural network involves the approximate solution as an iterative form of strategy. A DenseNet encoder-decoder framework with attention units is used to extract features robustly and a noise-prior subnetwork uses the distortion properties to modify suppression strategies. Training is based on a multi-objective loss that is an assembly of Mean Squared Error (MSE), Structural Similarity Index (SSIM), edge-preserving loss and regularization. Experimental results on BSD500 and cross-dataset testing reveal better performance with the proposed model which offers higher average PSNR of 30.9 dB, SSIM of 0.927 and Noise Reduction Rate of 92% than the state-of-the-art baselines of DnCNN, DeblurGAN and Restormer. The model further provides competitive inference time of 28.7ms per image, which is applicable in the real-time. The findings show that neural optimization is useful in balancing fidelity, sharpness of perception, and strength across heterogeneous conditions. The study provides a scalable and efficient way of restoring images, which would lead to an improved application in real-world scenarios where clarity of the visuals is very important.
Design and development of autonomous and unmanned vehicles for submarine applications Swapna B., Kamalahasan M., Kavitha G., Sujitha M., S. Reshma Chandran, Surendiran Muthukumar D., Bhuvaneswari S. Emerging Advancements in AI and Big Data Technologies in Business and Society, 2024 AUVs are robotic submarines that are a part of the emerging field of autonomous and unmanned vehicles. This project shows the design implementation of an AUV as a miniature size and its test bed platform for a variety of research in underwater technologies especially involving small-scale, surface water, and low-cost underwater robots. The general design and its consideration are well discussed in this chapter. The AUV prototype has been developed by SolidWorks. It will have a fixed mechanical system and body, having a modular electronic system that allows the development of various controllers. The controller and motors have been tested in small-scale surface water, and the result is encouraging. Some factors affecting AUV performance are also elaborated for future research in this area. Underwater robots can explore areas of the ocean that are too dangerous or too difficult for humans to go.
Design and implementation of on-board computer sub-system for picosat B. Swapna, P. Amudhan, S. Gayathri, E. Kavitha, M. Kamalahasan, K. Saravanan, M. Sujitha Handbook of Research on Advancements in AI and Iot Convergence Technologies, 2023 Satellite tracking and control module in charge of maintenance is the subsystem. Monitoring and control of satellite locations affect the environment. Satellites are subjected to torque. This causes alignment and satellite angle instability while it is in space. The project involves the implementation of a satellite system and a test tool technology platform able to have it for lunch in the near future. It is also aimed towards them. Investigate the use of low-cost cube sats in the realm of remote sensing. In the original iteration of their design, the cube satellite utilized Picosat passive attitude control. However, a new version has been released to fulfil the accuracy standards of Picosat, the primary payload, which was supposed to be active attitude control. New posture determination and control the subsystem is in charge of successfully de-tumbling Picosat after booting and keeping it pointed in the right direction. As much as feasible, the desired alignment. This chapter describes the concept and execution of strong decision-making.
Identification of Nutrients and Microbial Contamination in Fruits and Vegetables - Technology Using Internet of Behavior K. Sujatha, N.P.G. Bhavani, G. Victo Sudha George, D. Kirubakaran, M. Sujitha, V. Srividhya Internet of Behavior Iob, 2023 In agricultural science, quality analysis of fruits and vegetables has been used to categorize color, shape, size and texture. The proposed technique will enable development of a smart phone app that uses intelligent image processing algorithms to scan the attributes of fruit exhibited in a supermarket and assess its nutritional values, like total carbohydrates, including sugars like glucose, fructose, and sucrose; potassium; magnesium; vitamins like vitamin A and vitamin C; and antioxidants, along with microbial contamination. This instant information received by customers, once they capture images of the fruit using a smart phone, will kindle their interest in purchasing fruits based on their needs. Another added feature of this smart phone app is that it will enable customers to identify microbial contamination in fruits and vegetables. Today, mobile phones have become part and parcel of our lifestyle, so that nearly everyone possesses one such device. This smart phone app, once developed, will be freely available through the Google Play store. Customers, who are the end users, need to have information about fruits and vegetables that will motivate them to purchase them. This simple, user-friendly technology will facilitate measurements related to nutritional value, which includes parameters like sugar content, carbohydrates, potassium, and vitamins, by embedding an intelligent image-processing algorithm that will process photos of various fruit captured by a camera in a smart phone. This advanced technology using a smart phone app extracts the color, shape, average intensity and sum of absolute difference for various fruits like mango, banana, orange, papaya, and tomato to classify them into three categories: high quality, medium quality, and low quality. This novel technology will put an end to the challenge involved in sorting the fruits and vegetables that can be cultivated using artificial fertilizers, which are harmful for consumption. Excessive usage of fertilizers not only decreases nutritional content but also reduces the taste and flavor of fruit.
Green Energy Implementation based on Smart Grid Technology M. Sujitha, Gangavath Veeranna, R. Venkatesh, S Srinidhi, Jarabala Ranga, L Malleswara Rao 2nd International Conference on Sustainable Computing and Data Communication Systems Icscds 2023 Proceedings, 2023 Utilizing solar, wind, and other biomass energy sources will not reduce these resources available in the future. In order to keep up with the ever-increasing need for energy, people are turning to the sun. This analysis emphasizes public opinion on renewable energy and addresses the world’s energy demands in light of the many renewable energy sources available for residential use. From 2009 to 2018, the literature was systematically reviewed. More than 300 publications were sorted into appropriate categories, and 42 studies were selected for in-depth evaluation. Despite widespread attempts to reduce reliance on fossil fuels and promote renewable energy, the literature assessment found that in 2017, energy sources accounted for 73.5% of the world’s largest power production. However, only 26.5% of the power needed could be met by renewable sources. Moreover, the study demonstrates that the public’s ignorance is a major barrier to the broad adoption of renewable energy. The findings of this study show that switching to renewable energy sources for electricity generation is an efficient way to deal with the world’s pressing energy needs. In addition, this comprehensive study has highlighted the value of public opinion and analyzed worldwide comments in real time to aid in the development of renewable energy technologies.
Novel and Optimized Efficient Transmission Using Dynamic Routing Technique for Underwater Acoustic Sensor Networks Swapna Babu, Bhuvaneswari Subramanian, Sujitha Madhavadhas, Kavitha Ganesan, Manjula Dhandapani, Surendiran Muthukumar Deva Engineering Proceedings, 2023 Underwater acoustic sensor networks involve deploying sensors underwater in order to establish a wireless network framework aimed at discovering new resources, detecting targets, and monitoring pollution.
Examination of the Recent Research Trends on Controllers in the AI Powered UAV B Swapna, A Lavanya, G Kavitha, M Sujitha, C Anuradha, ... Humans and Generative AI Tools for Collaborative Intelligence, 285-300 , 2025 2025
THE CONSEQUENCES OF SELF-MEDICATION SUGGESTED BY PHARMACISTS VERSUS DOCTORS'PRESCRIPTIONS J Nalinidevi, T Pradeep, D Manjula, G Kavitha, B Swapna, M Sujitha Int J Acad Med Pharm 7 (1), 777-782 , 2025 2025
Optimistic Machine Learning Algorithm to Identify Producer and Consumer Risks in the Medical Field Using Double Sampling Plan B Swapna, D Manjula, G Uma, G Kavitha, D SenthilKumar, M Sujitha, ... Convergence of Internet of Medical Things (IoMT) and Generative AI, 477-494 , 2025 2025
Design and Development of Autonomous and Unmanned Vehicles for Submarine Applications B Swapna, M Kamalahasan, G Kavitha, M Sujitha, ... Emerging Advancements in AI and Big Data Technologies in Business and … , 2024 2024 Citations: 1
Novel and Optimized Efficient Transmission Using Dynamic Routing Technique for Underwater Acoustic Sensor Networks S Babu, B Subramanian, S Madhavadhas, K Ganesan, M Dhandapani, ... Engineering Proceedings 59 (1), 89 , 2023 2023
Identification of Nutrients and Microbial Contamination in Fruits and Vegetables–Technology Using Internet of Behavior K Sujatha, NPG Bhavani, GVS George, D Kirubakaran, M Sujitha, ... Internet of Behaviors (IoB), 157-169 , 2023 2023 Citations: 1
Green Energy Implementation based on Smart Grid Technology M Sujitha, G Veeranna, R Venkatesh, S Srinidhi, J Ranga, LM Rao 2023 International Conference on Sustainable Computing and Data … , 2023 2023
Deep Learning Neural Networks for Detection of Onset Leukemia from Microscopic Images K Sujatha, NPG Bhavani, V Srividhya, B Latha, M Sujitha, U Jayalatsumi, ... International Conference on Communications and Cyber Physical Engineering … , 2023 2023 Citations: 1
Design and Implementation of On-Board Computer Sub-System for Picosat B Swapna, P Amudhan, S Gayathri, E Kavitha, M Kamalahasan, ... Handbook of Research on Advancements in AI and IoT Convergence Technologies … , 2023 2023
Design and Development of Writing Robot Using Speech Processing SERY Swapna B, Sujitha M, Reshma Chandran S, Surendiran Muthukumar D, Sunil ... Tuijin Jishu/Journal of Propulsion Technology 44 (4), 5811-5816 , 2023 2023
ZIGBEE BASED REALTIME PLANT MONITORING SYSTEM USING µC/OSII. M Sujitha, V KANNAN Journal of Theoretical & Applied Information Technology 65 (1) , 2014 2014 Citations: 1
RTOS IMPLEMENTATION OF NON-LINEAR SYSTEM USING MULTI TASKING, SCHEDULING AND CRITICAL SECTION M Sujitha, V Kannan, S Ravi Journal of Computer Science 10 (11), 2349-2357 , 2014 2014 Citations: 1
Memory Allocation Strategies for Real Time Operating System M SUJITHA, V KANNAN International Journal in Computational Intelligence 5 (02), 60-66 , 2014 2014
MOST CITED SCHOLAR PUBLICATIONS
Design and Development of Autonomous and Unmanned Vehicles for Submarine Applications B Swapna, M Kamalahasan, G Kavitha, M Sujitha, ... Emerging Advancements in AI and Big Data Technologies in Business and … , 2024 2024 Citations: 1
Identification of Nutrients and Microbial Contamination in Fruits and Vegetables–Technology Using Internet of Behavior K Sujatha, NPG Bhavani, GVS George, D Kirubakaran, M Sujitha, ... Internet of Behaviors (IoB), 157-169 , 2023 2023 Citations: 1
Deep Learning Neural Networks for Detection of Onset Leukemia from Microscopic Images K Sujatha, NPG Bhavani, V Srividhya, B Latha, M Sujitha, U Jayalatsumi, ... International Conference on Communications and Cyber Physical Engineering … , 2023 2023 Citations: 1
ZIGBEE BASED REALTIME PLANT MONITORING SYSTEM USING µC/OSII. M Sujitha, V KANNAN Journal of Theoretical & Applied Information Technology 65 (1) , 2014 2014 Citations: 1
RTOS IMPLEMENTATION OF NON-LINEAR SYSTEM USING MULTI TASKING, SCHEDULING AND CRITICAL SECTION M Sujitha, V Kannan, S Ravi Journal of Computer Science 10 (11), 2349-2357 , 2014 2014 Citations: 1
Examination of the Recent Research Trends on Controllers in the AI Powered UAV B Swapna, A Lavanya, G Kavitha, M Sujitha, C Anuradha, ... Humans and Generative AI Tools for Collaborative Intelligence, 285-300 , 2025 2025
THE CONSEQUENCES OF SELF-MEDICATION SUGGESTED BY PHARMACISTS VERSUS DOCTORS'PRESCRIPTIONS J Nalinidevi, T Pradeep, D Manjula, G Kavitha, B Swapna, M Sujitha Int J Acad Med Pharm 7 (1), 777-782 , 2025 2025
Optimistic Machine Learning Algorithm to Identify Producer and Consumer Risks in the Medical Field Using Double Sampling Plan B Swapna, D Manjula, G Uma, G Kavitha, D SenthilKumar, M Sujitha, ... Convergence of Internet of Medical Things (IoMT) and Generative AI, 477-494 , 2025 2025
Novel and Optimized Efficient Transmission Using Dynamic Routing Technique for Underwater Acoustic Sensor Networks S Babu, B Subramanian, S Madhavadhas, K Ganesan, M Dhandapani, ... Engineering Proceedings 59 (1), 89 , 2023 2023
Green Energy Implementation based on Smart Grid Technology M Sujitha, G Veeranna, R Venkatesh, S Srinidhi, J Ranga, LM Rao 2023 International Conference on Sustainable Computing and Data … , 2023 2023
Design and Implementation of On-Board Computer Sub-System for Picosat B Swapna, P Amudhan, S Gayathri, E Kavitha, M Kamalahasan, ... Handbook of Research on Advancements in AI and IoT Convergence Technologies … , 2023 2023
Design and Development of Writing Robot Using Speech Processing SERY Swapna B, Sujitha M, Reshma Chandran S, Surendiran Muthukumar D, Sunil ... Tuijin Jishu/Journal of Propulsion Technology 44 (4), 5811-5816 , 2023 2023
Memory Allocation Strategies for Real Time Operating System M SUJITHA, V KANNAN International Journal in Computational Intelligence 5 (02), 60-66 , 2014 2014
