Dr.T.Muthumanickam

@vmkvec.ac.in

Professor/Electronics and Communication Engineering
Vinayaka Missions Kirupananda Variyar Engineering College



              

https://researchid.co/muthu12

EDUCATION

B.E.,MTech,PhD

RESEARCH INTERESTS

VLSI Design

32

Scopus Publications

169

Scholar Citations

6

Scholar h-index

3

Scholar i10-index

Scopus Publications

  • Intelligent Robotic Medical Assistive Device for Elderly Individuals Support
    Chandrashekhar Kumar, Muthumanickam T., and Sheela T.
    Seventh Sense Research Group Journals

  • Analysis of Artificial Intelligence Industry 4.0 Automation Based Developments and its Applications
    Niranjan Sudhakar Deshmukh, P. Shalini, J.Madhuri Sailaja, Buddhaghosh Arjun Shingade, T. Muthumanickam, Pranav Kodali, and G. Ramachandran
    IEEE
    The days, manufacturers across a range of industries must handle increasingly difficult responsibilities including risk management, increasing efficiency and security, etc. Integration founded on Industry 4.0 concepts is one way to address these issues. The article explains Industry 4.0's constituent parts and fundamental ideas. Towards a structure to evaluate industry 4.0 services and technology's effect on production resources industrial 4.0 is becoming more and more significant in the manufacturing sector. Scholarly writings have mostly focused on the technological aspects of Industry 4.0. Studies that address Industry 4.0 technologies, services, and production resources within an industrial setting are, nevertheless, extremely rare. Specifically, there is a lack of research to support an academic conversation about how Industry 4.0 technologies affect its production resources and services. The purpose of this article is to provide an initial framework that illustrates how Industry 4.0 services and technologies affect production resources. Two distinct industries are the focus of the application of the framework. For industrial decision-making, this study can be utilized to better support and choose appropriate Industry 4.0 technology.

  • Adaptive Digital Beam Forming for Massive Array Employed in the XOR MUX full Adder FPGA Implementation
    Thamilazhagan T, T. Muthumanickam, T. Sheela, G. Suresh Kumar, and G. Ramachandran
    IEEE
    Improving the quality of communication is very necessary with recent technology. Include the building of 5G wireless networks and growth of various communication tools. A method known as adaptive digital beam forming is one that adjusts an antenna’s radiation pattern array inside response to a particular signal reception that is desired. An adaptation this is based on (LMS) and its variant continues to be one of creative strategies that are employed the most. The improvement of antennas has led to the creation of high-performance hardware, even though those LMS techniques provide impressive computing performance. Systems like (FPGAs)-Field Programmable Gate Arrays, which were developed used for large array system, provide designs that are both high-performance and efficient with regard to energy consumption. The proposed work in this study presents a parallel implementation of a vast array beam forming system utilizing LMS on FPGAs with conventional and XOR-MUX full adder designs. The beam-forming system consists of a spatial filter and an adaptation unit. This proposed work was developed at Verilog HDL, synthesized on a Xilinx A vertex- 5 FPGA, and evaluated every parameter concerning area, latency, and power consumption.

  • Energy-Efficient ECG Signal Processing based on Approximate Pruned Haar Discrete Wavelet Transform Implemented on FPGA
    R. Ragavi, T. Sheela, T. Muthumanickam, G. Suresh Kumar, and G. Ramachandran
    IEEE
    One of the most commonly used instruments for the diagnosis and evaluation of epilepsy is the electroencephalogram (EEG). Currently, epilepsy be diagnosed mostly by a neurological specialist via visual or manual EEG examination readings. This study proposes an epilepsy computer-aided diagnostics (CAD) based on the Feed-Forward Neural Network (FFNN), Discrete Wavelet Transform (DWT), and Shannon entropy. DWT divides EEG impulses into numerous sub-bands of frequency that consist of gamma, beta, alpha, theta, and delta. Shannon entropy extracts ECG information from every frequency sub-band. Lastly, FFNN uses the collected features to classify the related EEG signals as "normal" or "epileptic". The outcomes of experiment with the accessible to the public Bonn University EEG dataset indicate the total precision.

  • Medical Accident Image Analysis Using Capsule Neural Network
    Chandrashekhar Kumar, T. Muthumanickam, and T. Sheela
    IEEE
    The rapid advancement of real-time medical technologies necessitates a focus on patient health, safety, and privacy. Reducing human intervention is essential due to age-related factors and the need for secure handling of sensitive information. This study explores the application of a Capsule Neural Network (Caps-Net) for real-time medical image recognition and analysis, a task traditionally enhanced by Convolutional Neural Networks (CNNs). Caps-Net is employed to identify and analyse injuries such as hand cuts, head and nose bleeding, and leg injuries from accidents. Utilizing a dataset of 12,000 images processed in Google Colab, the proposed model achieved a remarkable accuracy of 97%. These results highlight CapsNet's efficacy in medical imaging, offering significant benefits to healthcare professionals by improving diagnostic accuracy and expediting patient care. This research highlights the potential of advanced AI technologies in transforming medical image processing and enhancing clinical outcomes.

  • Analysis of IoT based Digital Waste Management Collections Garbage Disposal and its Applications
    K. Periyasamy, Peram Praveen Kumar Reddy, Sonukumar, G. Ramachandran, and T. Muthumanickam
    IEEE
    Given the hazardous nature of heavy metals and chemicals in used electrical and electronic equipment (e-waste), effective management has become integral to solid waste management practices. The presence of valuable metals like gold and copper underscores the importance of efficient waste treatment methods. This study proposes a smart collecting system for managing and recycling household e-waste in India. The system includes a smart collecting box equipped with sensors to monitor e-waste levels and log disposal details. An IoT automated back-end server is employed to detect and schedule the dispatch and collection of e-waste collectors when the collection box reaches eighty percent capacity. Additionally, a mobile application allows public end users to dispose of their household e-waste conveniently. The proof-of-concept for the smart system has been successfully established, promising improvements in how India collects household waste and consumer electronics.

  • Analysis of Internet of Things Based Agriculture Fertilizer Nutrient Management Soil Health Irrigation System and its Applications
    S. Venkatachalam, P. Kavitha, Pradnya Kirankumar Ingle, G. Ramachandran, R. Sasikala, and T. Muthumanickam
    IEEE
    Crops require irrigation in order to grow, and irrigation promotes economic growth gradually. The time required for an effective water flow to the crop fields will be determined by the combinations of these parameters. An essential component of the production of agricultural products is irrigation. Moreover, the current sky circumstances are specified by earlier study, which yields results that are 95 percent accurate. The agronomic design, which determines the quantity of water required for each crop, is an additional task. An irrigation system based on fuzzy rules has been devised for the other research. However, the proposed model has an additional feature: a rain sensor. It makes use of to get around the problem of irregular irrigation activation. The other feature that activates the spray on the region when the farmer flips on the fertilizer button is fertilizer control.

  • Early detection of analog circuit performance using RBF
    M. P. Varghese and T. Muthumanickam
    AIP Publishing


  • Analysis of Unmanned Four-Wheeled Bot with AI Evaluation Feedback Linearization Method
    Chandrashekhar Kumar and T. Muthumanickam
    Auricle Technologies, Pvt., Ltd.
    In this research paperwork, thereis the design and implementation of aBot with the ability to work in four directions of movement forward, backward, left, and right using aself-governingstability system. The bot's resultingbe in command of objective is to follow a path at the required speed, while its primary control purpose is to maintain equilibrium whenever the balance position is unstable owing to a change in the center of gravity. We report our surveys into the concertevaluation of a highly linear four-wheeledmatchingmachine using a PID regulator and a PI-PD regulator.  Here I have added advantages with the AI evaluation feedback linearization technique to detect and process with auto error time solutions. The key benefits include cogency in the actual application; switchdevice, enhanced performance, and capacity to overcome uncertainties. Simulated and experimental findings are used to compare and support a performance evaluation of the system. Numerous automatic systems for detecting traffic accidents have been developed by researchers. These techniques frequently make use of many applications such as smartphones, infrared sensors, and mobile applications.All of these techniques fall short when it comes to the instinctiverecognition of traffic accidents. The sifters used in smartphones may make it difficult to detect low-speed collisions. The suggested system does not specify the threshold distances at which an IR sensor will react. It is suggested to use a revolutionary method based on ultrasonic sensors.Using an ultrasonic sensor to identify accidents allows for the ability to do so not only in different street contexts but also in industrial settings, busy intersections, and weather circumstances like clouds, fog weather, rain, and heavy traffic.

  • Analysis of Wireless Internet of Things to Medical Health Care Patient Applications
    K Aravinda, L. Manjunath, S. Elango, S. Krishnaveni, G. Ramachandran, PM Murali, and T. Muthumanickam
    IEEE
    The patients and older people with serious conditions, the failure to take medications as prescribed can be quite dangerous to their health. Using IoT A medical caretakers is suggested as a solution to that issue. The purpose of this pillbox is to assist patients in taking the right medications at the proper dosage at the appropriate times while also helping to record the patient's medical history. The pillbox can be configured using an app, and once the patient presses. Additionally, it will maintain the pill count and provide an alert when the quantity is low. Thus, the purpose of this clever pillbox is to make patients' lives easier while maintaining their health. The need for healthcare is increasing due to the growing world population, increasing expectations for effective treatment, and a general rise in life satisfaction. As a result, the development of new and more advanced scientific and technology therapies is required because healthcare continues to be one of the biggest social and economic challenges in the world.

  • Artificial Intelligence for Development of Variable Power Biomedical Electronics Gadgets Applications
    A. Celina, Vijilius Helena Raj, V.K. Ajay, G. Ramachandran, Chandrashekhar Kumar, and T. Muthumanickam
    IEEE
    The use of artificial intelligence (AI) technology in computers has increased recently, as evidenced by the numerous research electronics goods. Many of these researchers have specialists who link and mix artificial intelligence (AI) in computers with electronic design. As a result, it makes it possible for a lot of researchers to continue researching the more advanced growth path of computer AI technology. It explores the features and value of computer AI technology in the design of electronic products in more detail and suggests that applying computer AI to the creation of electronic products is challenging. Additionally, this essay highlights the pertinent techniques and approaches for using AI in the creation of electronic products. Additionally, this can broaden the applications of computer AI technology, which is now the cornerstone of study into the design of electronic products.

  • Semi Autonomous Robot for Domestic purpose
    Muhammed Shafi, S.Sheik Mohammed, T. Sheela, T. Muthumanickam, and G.Suresh Kumar
    IEEE
    Today, technology is rapidly advancing to meet the growing needs of humanity, with a particular focus on robots. Robotics refers to the creation of machines that can perform tasks or actions typically done by humans, either autonomously or via remote control. One of the major advantages of robots is their ability to operate in hazardous environments that are unsafe for humans. As a result, scientists are continually seeking to improve robots by developing new controllers and designs to make them more efficient and reliable. Our mini project centers around categorizing home robots based on the specific task they are designed to perform. The categorization is based on the object of operation. Our system features a semi-humanoid robot prepared with Google Assistant to interact with humans and carry out tasks according to our commands. The robot has the ability to move in different directions, halt, grip and release objects, and move its arms vertically. Furthermore, it includes a built-in vacuum cleaner feature that permits the robot to tidy floors.

  • Artificial Intelligence based Electronics Engineering Software Application System
    Thiagarajan Kittappa, C. Sandhya, V. Krishnan, Shilpa Sharma, Deepti Khubalkar, G. Ramachandran, and T. Muthumanickam
    IEEE
    Science and technology are in a rapid development stage as a result of the advancement and progress of the times, and it is clear that the contemporary civilization has entered the era of Artificial Intelligence (AI). This research focuses on AI applications in the context of Industry 4.0 concept. This current work discusses AI acceptance in the manufacturing industry and its promotion in intelligence optimization. The Virtual model concept is presented to improve the rationale of various interfaces. The communication and information intelligence AI algorithms are examined in depth. The concept of a smart city and AI applications, as well as how AI plays a role in its implementation have been discussed.

  • Analysis the performance Medical Pharma Information System Applications
    Chandrashekhar Kumar and T. Muthumanickam
    IEEE
    Over the years, the Indian pharmaceutical business has been the most awaited around the world. It is the world's largest supplier of medical facilities and a leader in pharmaceutical manufacture. The Internet of Things offers the pharmaceutical business a variety of new individualised market prospects, a more controlled environment for pharma manufacturing, the ability to avoid equipment maintenance, and a more varied supply chain management system. Pharmaceutical manufacturing may be unable to provide benign and safe medicinal production and circulation due to transparency issues. Adoption of the internet of things could give pharma companies using pharma IoT a new competitive advantage. This is a conceptual exploratory investigation that shows the future of Indian pharmaceuticals, which is on the point of being self-sufficient. Customers wearing internet-connected digital devices and sensors implanted in wearable's could be tracked using the internet of things, artificial intelligence, big data analytics, and tracking of customers carrying internet-connected digital devices and sensors implanted in wear ables. This would also serve as a warning to both clinical makers and consumers, allowing for the development of tailored products and a brighter future for the Indian pharmaceutical industry. Future Pharma would transform production by employing better, more reliable vast volumes of data to link paraphernalia throughout development and distribution.

  • Development of Animal-Detection System using Modified CNN Algorithm
    Sheik Mohammed. S, T. Sheela, and T. Muthumanickam
    IEEE
    In the present scenario almost the entire crop cultivation in farmlands are mostly likely to be damaged by intrusion of animals like wild boars, elephants, buffaloes, birds, etc. However this may cause huge loss to the farmers but it is quite impossible to stay alert in the farm field for 24/7 hours to protect the crops. To surmount the above problem, a prototype for animal intrusion detection has been designed using a modified CNN algorithm to efficiently detect the existence of animal intrusion in the crop field. It provides an alert signal to indicate while averting the animal with no injuries. This paper proposes a system that includes a PIR sensor, Thermal Imaging camera, GSM module and hologram connected with the Raspberry Pi module. A Modified CNN algorithm is used to validate the captured animal image and later alert the user. Absolute crop protection is guaranteed from animal trespass thereby protecting the farmer's from huge loss.

  • Artificial Intelligence System based Embedded Real-Time System Power Optimization and Adaptability
    Nilamani Ganesan and T. Muthumanickam
    IEEE
    This research study focuses on finding solutions to the emerging challenges in the embedded systems' power consumption optimization. First, the challenges in physical CMOS power consumption are analyzed and further various real-time limitationsand load characteristics are explored. Further, various power consumption techniques are considered by including DMP, DVS/DFS, AVS, and ABB. Issues with organising a feedback and determining adaptability for various embedded systems are investigated.

  • Analysis of Artificial Intelligence in Medical Sectors
    J Thilagavathi, K Lavanya, S. Elango, M. Santhoshi, T. Muthumanickam, and G. Ramachandran
    IEEE
    Medical engineering research has recently advanced significantly. The ability to accurately record a significant amount of medical data has increased because to advancements in measuring device technology, which has caused medical data to rise rapidly. A significant amount of data has been encountered and it is crucial to use this enormous amount of data sensibly. By using an Artificial Intelligence (AI) based reasoning engine to scan medical data, it is possible to compile user-generated keywords and instantly suggest relevant content to users. The decision tree algorithm is emphasized as one of the main technologies to implement data mining in this research, and it also explores how data mining technology is used in clinical medical diagnosis mining and analysis.

  • IoT Enabled Health Monitoring System using Machine Learning Algorithm
    Sheik Mohammed. S, T. Sheela, and T. Muthumanickam
    IEEE
    Now-a-davs Internet of Things (IoT) is used in various real-time applications, Including smart health monitoring. The existing health monitoring system can only collect the basic information about heat. heartbeat. and BP (Blood Pressure). This research study proposes an effective examination of patient's brain signals and detect the health status of the patient in real time. The main objective of the proposed study is to provide a proper optimized value about the mentally challenged patients by collecting the data information from brain signals with 24 channels and study the body parameters through each EEG (Electroencephalography) signal channel. Here, the collected data is pre-processed by using Machine Learninz (ML) tools and Neural Networks (NN) with Python programming language, By collecting the data information from brain signals with EEG sensors, an optimized value and solution can be provided to the patients suffering from Cerebral Palsy (CP). The collected data is then stored in a cloud storage platform and it can be accessed from any remote location. The stored data is then collected and filtered by using PCA techniques and further the Artifact siznals (Noise) are removed to diagnose seizures by Identifying brain signal parameters (Alpha, Beta, Delta and Theta). Further, a novel model has been designed by using python programming languaze for training the machine with a maximum number of datasets in order to check accuracy and predict the seizure levels of any CP patient. Neural Network (NN) algorithms were applied here by using python programming language in order to check the percentage error in the data processing mechanism. Once the data is analyzed with the proposed model it suggests the CP patient for Tentative Treatment.

  • Machine Learning Approaches for Electronic Design Automation in IC Design Flow
    M P Varghese and T. Muthumanickam
    IEEE
    Due to the vast amount of data collected and the very high level of complexity in VLSI design and manufacturing, the implementation using machine learning can be used in physical design has increased significantly. ML can be used to increase the abstraction level that is obtained from complex simulations based on physics models and provide results that represent a significant level of quality. Computer science techniques such as pattern matching and machine learning can reduce the design time of VLSI circuits by working with large datasets.

  • VLSI Low Power Design Analysis Modeling Strategies


  • Investigation to Improve Reliableness for Health Monitoring in Different Environments using MEMS based Higher Sensitive Microcantilever Array
    Kaustubh Kumar Shukla, T. Muthumanickam, and T. Sheela
    IEEE
    Enhancement of reliability and sensitivity plays a vital role in Micro-Electro-Mechanical Systems (MEMS) technology, and it can be done very effectively by reducing the failures (through minimization) of such kind of systems. As it is a much known fact that using micro fabrication technique product development is not so easy because of its high cost and such facilities are not available everywhere. In this research work the primary focus is to know about the trust-worthiness of MEMS based devices by designing and performance analysis through simulation in multiphysics environment. The main outcome of this work is to model a novel device with high reliability as well as sensitivity which are very useful for healthcare monitoring and related applications in different environments. Through literature survey several reliability problems like stiction, fractural defects, immobilization, structural instability and many more has been noticed and possible solutions has been investigated which has been tested and analyzed in multiphysics environment. In this paper several micro-shapes and micro- structures has been designed and tested using different sensing materials but end of the result it has been found that microcantilever arrays are more useful and simple. Apart from this it has been also noticed that microcantilever has high reliability and sensitivity, it has been compared by applying some pressure to achieve maximum displacement. So, this research work is recommending microcantilever array sensor for different health care applications because of its high sensitivity, selectivity, high reliability, simplicity and versatility with different medium.

  • A smart sensor using MEMS technology for artificial environmental monitoring
    Kaustubh Kumar Shukla and T. Muthumanickam
    Elsevier BV

  • Micro Cantilever Arrays Optimization and Analysis for Healthcare Applications
    Kaustubh Kumar Shukla and T. Muthumanickam
    IEEE
    Presently engineering science plays a critical part in the environmental monitoring and healthcare. Through this research effort an array of micro cantilever is designed and analyzed with the help of Micro-Electro-Mechanical -Systems (MEMS) technology. Aim of this study is device should be easy to design, consume less energy, be simple to model, and be cost-effective and efficient. As a result, micro cantilevers are the perfect platform to explore for such issues because they can be employed as a very sensitive element in a variety of applications and different environment. Instead of a micro cantilever, a micro cantilever array has been modeled to improve the sensitivity. Because the device's output should be high, several types of studies have been carried out, including the use of nine unlike materials and accordingly the improvement in the sensitivity, as a conclusion SiO2 is the best choices for maximum displacement. Aside from that, several geometrical shapes built and analyzed for improved sensitivity in the form of maximum displacement. During the analysis process, a few facts emerged, such as how to make micro cantilever arrays simple and cost-effective. Instead of utilising three micro cantilevers as arrays, two micro cantilevers with the same efficiency can be utilized by adjusting the forces on the arrays' surfaces. Improved sensitivity and utmost displacement can be achieved by reducing effective areas across fixed end utilizing different geometrical variations. This inquiry report could be relevant in the development of a micro cantilever biosensor for the detection of various diseases.

  • Investigation through the Analysis of Double Strip Micro Cantilever for the Identification of Cancer at Early Stage
    Kaustubh Kumar Shukla and T. Muthumanickam
    IEEE
    A huge popularity of biosensors is because of its detection capability of bio molecules. Micro cantilevers are adding some additional features in this detection technique with the help of MEMS (Micro-Electro-Mechanical-Systems) technology. In this paper single, double and 3-strip microcantilevr has been designed and analyzed. The primary principle of this paper is to identify the bio molecule using the deflection of beam. Due to colliding of targeted molecules with sensing layer at free end of the microcantiliver enhancement of weight occurs as a result micro cantilever get bends. This bending provides a very important result that is how to detect the presence of cancer in the blood cells. It may be analyzed either in dynamic or static mode of micro cantilever. This research work is not providing a solution of how to be get cured from this disease but it is providing a suitable solution of how the cancer can be detected at its initial stage using a small amount of blood samples. Since, DNA (Deoxyribonucleic acid) and image based cancer detection techniques are very expensive and complicated; it is why this Micro-Electro-Mechanical Systems based micro cantilever technique has been suggested in this work. Additional advantage is since these devices are micro scale devices, thus very small amount of blood sample is required to test and identify the target molecules. Selection of a suitable sensing material is further additional benefits for this research and it has a huge scope.

RECENT SCHOLAR PUBLICATIONS

  • Analysis of Artificial Intelligence Industry 4.0 Automation Based Developments and its Applications
    NS Deshmukh, P Shalini, JM Sailaja, BA Shingade, T Muthumanickam, ...
    2024 IEEE 4th International Conference on Applied Electromagnetics, Signal 2024

  • Medical Accident Image Analysis Using Capsule Neural Network
    C Kumar, T Muthumanickam, T Sheela
    2024 2nd International Conference on Sustainable Computing and Smart Systems 2024

  • Energy-Efficient ECG Signal Processing based on Approximate Pruned Haar Discrete Wavelet Transform Implemented on FPGA
    R Ragavi, T Sheela, T Muthumanickam, GS Kumar, G Ramachandran
    2024 Second International Conference on Inventive Computing and Informatics 2024

  • Adaptive Digital Beam Forming for Massive Array Employed in the XOR MUX full Adder FPGA Implementation
    T Thamilazhagan, T Muthumanickam, T Sheela, GS Kumar, ...
    2024 Second International Conference on Inventive Computing and Informatics 2024

  • Analysis of IoT based Digital Waste Management Collections Garbage Disposal and its Applications
    K Periyasamy, PPK Reddy, G Ramachandran, T Muthumanickam
    2024 3rd International Conference on Applied Artificial Intelligence and 2024

  • Analysis of Internet of Things Based Agriculture Fertilizer Nutrient Management Soil Health Irrigation System and its Applications
    S Venkatachalam, P Kavitha, PK Ingle, G Ramachandran, R Sasikala, ...
    2024 2nd International Conference on Intelligent Data Communication 2024

  • Early detection of analog circuit performance using RBF
    MP Varghese, T Muthumanickam
    AIP Conference Proceedings 2917 (1) 2023

  • Analysis of Wireless Internet of Things to Medical Health Care Patient Applications
    K Aravinda, L Manjunath, S Elango, S Krishnaveni, G Ramachandran, ...
    2023 First International Conference on Advances in Electrical, Electronics 2023

  • Artificial Intelligence for Development of Variable Power Biomedical Electronics Gadgets Applications
    A Celina, VH Raj, VK Ajay, G Ramachandran, C Kumar, ...
    2023 Second International Conference on Augmented Intelligence and 2023

  • AI-based drone system for medical support in congested areas
    C Kumar, T Muthumanickam
     2023

  • Semi autonomous robot for domestic purpose
    M Shafi, SS Mohammed, T Sheela, T Muthumanickam, GS Kumar
    2023 International Conference on Sustainable Computing and Data 2023

  • Artificial Intelligence based Electronics Engineering Software Application System
    T Kittappa, C Sandhya, V Krishnan, S Sharma, D Khubalkar, ...
    2023 5th International Conference on Smart Systems and Inventive Technology 2023

  • Analysis of unmanned four-wheeled bot with AI evaluation feedback linearization method
    C Kumar, T Muthumanickam
    International Journal on Recent and Innovation Trends in Computing and 2023

  • Analysis the performance Medical Pharma Information System Applications
    C Kumar, T Muthumanickam
    2022 International Conference on Power, Energy, Control and Transmission 2022

  • IoT Enabled Health Monitoring System using Machine Learning Algorithm
    T Sheela, T Muthumanickam
    2022 6th International Conference on Electronics, Communication and 2022

  • Analysis of Artificial Intelligence in Medical Sectors
    J Thilagavathi, K Lavanya, S Elango, M Santhoshi, T Muthumanickam, ...
    2022 International Conference on Augmented Intelligence and Sustainable 2022

  • Development of animal-detection system using modified CNN algorithm
    T Sheela, T Muthumanickam
    2022 International Conference on Augmented Intelligence and Sustainable 2022

  • Artificial Intelligence System based Embedded Real-Time System Power Optimization and Adaptability
    N Ganesan, T Muthumanickam
    2022 International Conference on Augmented Intelligence and Sustainable 2022

  • Machine learning approaches for electronic design automation in IC design flow
    MP Varghese, T Muthumanickam
    2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile 2022

  • Investigation to improve reliableness for health monitoring in different environments using MEMS based higher sensitive microcantilever array
    KK Shukla, T Muthumanickam, T Sheela
    2022 2nd International Conference on Emerging Frontiers in Electrical and 2022

MOST CITED SCHOLAR PUBLICATIONS

  • An effective motion object detection using adaptive background modeling mechanism in video surveillance system
    MT Kalli Siva Nagi Reddy , Suresh T, Prasanth A
    Journal of Intelligent & Fuzzy Systems 41 (1), 1777-1789 2021
    Citations: 50

  • Performance Analysis of a Bottleneck Layer Network in the Estimation of Cyber-Attacks
    T Muthumanickam, DV Kumar
    2022 6th International Conference on Computing Methodologies and 2022
    Citations: 10

  • Animal health monitoring system using Raspberry Pi and wireless sensor
    L Narayan, DT Muthumanickam, DA Nagappan
    International Journal of Scientific Research and Education (IJSRE) 3 (5) 2015
    Citations: 10

  • A smart sensor using MEMS technology for artificial environmental monitoring
    KK Shukla, T Muthumanickam
    Materials Today: Proceedings 66, 3626-3633 2022
    Citations: 8

  • Simulation Transfer of Files from PC To PC Using LAN Trainer Kit
    G Ramachandran, T Muthumanickam, T Sheela, R Thirunavukkarasu
    International Journal of Trend in Research and Development, Volume 2(2 2015
    Citations: 6

  • PERFORMANCE ANALYSIS OF CRYPTOGRAPHIC VLSI DATA
    T Muthumanickam., TS A. Nagappan.
    IRACST – International Journal of Computer Networ ks and Wireless 2012
    Citations: 6

  • Development of animal-detection system using modified CNN algorithm
    T Sheela, T Muthumanickam
    2022 International Conference on Augmented Intelligence and Sustainable 2022
    Citations: 5

  • Investigation to improve reliableness for health monitoring in different environments using MEMS based higher sensitive microcantilever array
    KK Shukla, T Muthumanickam, T Sheela
    2022 2nd International Conference on Emerging Frontiers in Electrical and 2022
    Citations: 5

  • Analysis of Artificial Intelligence in Medical Sectors
    J Thilagavathi, K Lavanya, S Elango, M Santhoshi, T Muthumanickam, ...
    2022 International Conference on Augmented Intelligence and Sustainable 2022
    Citations: 4

  • Micro Cantilever Arrays Optimization and Analysis for Healthcare Applications
    KK Shukla, T Muthumanickam
    2022 International Conference on Applied Artificial Intelligence and 2022
    Citations: 4

  • Effects of Thermally Induced Deformations and Surface Radiosity for 3D Heat Transfer and Its Applications
    KK Shukla, T Muthumanickam, T Sheela
    Technology Innovation in Mechanical Engineering: Select Proceedings of TIME 2022
    Citations: 4

  • Automation using Artificial intelligence based Natural Language processing
    P Mohana, M Muthuvinayagam, P Umasankar, T Muthumanickam
    2022 6th International Conference on Computing Methodologies and 2022
    Citations: 4

  • Application of coagulation and flocculation of water and reuse wastewater treatment in agriculture
    R Sethupathi, CK Dixit, VV Babu, G Ramachandran, A Arunraja, ...
    AIP Conference Proceedings 2396 (1) 2021
    Citations: 4

  • Study and Analysis of MEMS based Micro-Cantilever Sensor and its Medical Applications
    MKK Shukla, T Muthumanickam, T Sheela
     2019
    Citations: 4

  • Study And Implementation Of Green Power In Campus Environment
    G Ramachandran, T MuthuManickam, B SuganyaAbiramavalli, T Sheela, ...
    International Journal of Electronics and communication Engineering 2012
    Citations: 4

  • Analysis of Internet of Things Based Agriculture Fertilizer Nutrient Management Soil Health Irrigation System and its Applications
    S Venkatachalam, P Kavitha, PK Ingle, G Ramachandran, R Sasikala, ...
    2024 2nd International Conference on Intelligent Data Communication 2024
    Citations: 3

  • MEMS Technology for Early Stage Diesis Detection Using Micro-Cantilever Structure in Support of Biomedical Applications
    KK Shukla, T Muthumanickam
    ECS Transactions 107 (1), 1125 2022
    Citations: 3

  • Review Paper on Implementation of Neural Network for FPGA System Design
    TM Varghese M P
    Indian Journal of Natural Sciences 11 (64), 1-7 2021
    Citations: 3

  • Design of MEMS based micro cantilever
    KK Shukla, T Muthumanickam, T Sheela
    Sensors and actuators 1, 5 2019
    Citations: 3

  • A LFSR based Binary Numeral System Using CMOS VLSI
    T Sheela, T Muthumanickam, A NAGAPPAN
    International Journal of VLSI and Embedded Systems-IJVES ISSN 1 (8), 2249-6556 2014
    Citations: 3