Selvakumar
@vit.ac.in
Head of Department - VIT FASHION INSTITUTE OF TECHNOLOGY
VELLORE INSTITUTE OF TECHNOLOGY
EDUCATION
B.Tech, M.Tech., PhD
RESEARCH INTERESTS
Metal Matrix Composite
CNT based composite
Yarn Friction
Characterization
Clothing Comfort
Textile Technology
Wearable Technology
FUTURE PROJECTS
wearable electronics
Embedded electronics for health care monitoring
Applications Invited
Industry tie up
Scopus Publications
Scopus Publications
A. Selvakumar and A. Balasundaram
Informa UK Limited
A. Arivarasi, D. Thiripurasundari, A. Arockia Selvakumar, Bhuvan Kumaar, T. Aghil, S. Rahul, and Ramani Kannan
AIP Publishing
Stroke represents a severe, widespread, and widely acknowledged health crisis on both national and international levels. It is one of the most prevalent life-threatening conditions. Despite impressive advances in treating stroke, in addition to a need for effective patient care services, many sufferers still rely solely on physical interventions. The present paper describes and explains the use of a newly designed gadget for stroke survivors who cannot move their fingers. This is a sophisticated mobile device that enables stroke patients to regain their muscle memory and thus their ability to perform repetitive actions by continuing to tighten and stretch their muscles without the intervention of a physiotherapist. Gamification methodology is used to encourage patients to become involved in the process of rehabilitation. The device also has sensors that take information and transmit it to an app through an ESP32 connection. This enables physicians to view glove usage information remotely and keep track of an individual patient’s health. Communication between app and glove is facilitated by a broker in the Amazon Web Service IoT. With the robotic glove presented here, the recovery rate is found to be 90.23% over four weeks’ duration, which represents a significant improvement compared with existing hospital-based rehabilitation techniques.
Devashish Sharma, Sahil Shaik, Hemang Parab, R. Saran, Manju Mohan, Pavan Lingampally, Kuppan Ramanathan, and Arockia Selvakumar
AIP Publishing
Puvis Srinet, Michael Short, and Arockia Selvakumar Arockia Doss
AIP Publishing
R. Muraliraja, R. Anthoni Sagaya Selvan, A. Selvakumar, M. Franco, T.R. Tamilarasan, U. Sanjith, Wei Sha, and Jothi Sudagar
Elsevier BV
Arockia Selvakumar Arockia Doss, Pavan Kalyan Lingampally, Gia Minh Thao Nguyen, and Daniel Schilberg
Elsevier BV
Michael Short, Andrew Kidd, Ghazal Salimi, Geetika Aggarwal, Ruben Pinedo-Cuenca, Alan Williamson, Ashley Tizard, and Arockia Selvakumar
IEEE
In the United Kingdom, industry accounts for roughly a quarter of greenhouse gas emissions. The UK Government has set ambitious net-zero targets committed to the decarbonisation of heavy industry, and the Industrial Clusters mission aims to establish the world's first net-zero carbon industrial cluster by 2040. To reduce the energy costs and carbon footprint of industry, one of the most effective solutions is the use of digital tools enabling businesses to monitor and visualize their energy consumption in real-time. Due to recent advancements in industrial digitalization, many industrial sites already generate data, including energy monitoring data, with varying degrees of digital maturity. However, a major challenge with this data is a lack of commercial tools for modeling, predicting, and visualizing industrial manufacturing energy data for efficiency improvement and emissions reduction. This paper describes efforts in a recently funded project to develop a prototype flexible, industrial energy efficiency, and visualization profiling Toolbox (I-CAT). The toolbox embeds energy analytics and Machine Learning (ML) capabilities into an existing commercial SCADA platform for industrial manufacturing operations. This approach allows the creation of an energy Digital Twin. The paper describes requirements of the toolbox, and experimental analysis of the toolbox in a case study, an operational sawmill in Carlisle, UK. Data-driven modeling allows the creation of a predictive model of the energy consumption of the facility from a forecasted production schedule. Mean average modeling errors of less than 10% were obtained. The paper concludes by highlighting areas of future development work.
Arockia Selvakumar Arockia Doss, Abarna Jeyabalan, Priti Rekha Borah, Pavan Kalyan Lingampally, and Ing. Daniel Schilberg
World Scientific Pub Co Pte Ltd
This paper discusses about the modern techniques implemented in the field of agriculture which shaped the traditional farming to the smart farming (Agriculture 4.0). The rapid rise in the global population is one among the main reasons, besides monitoring of crops health and yield requires a huge labor force, which is also another reason for promoting intelligent systems into agriculture sector. Conventional farming methods are not suitable to meet this demand, which led robotics to associate with on-field agriculture by means of robot-based technologies like wheeled robots, ground vehicles (manned and unmanned) and aerial vehicles (manned and unmanned) that led to explore the possible advancement in agriculture 3.0. Currently, the evolutionary techniques, such as Artificial Intelligence (AI) and IoT, are implemented in robotic vehicles to make them intelligent systems. Due to unprecedented climatic change and polluted ground water for the past few decades, the crops are being infested with new varieties of diseases. This requires new image processing techniques to classify the diseases based on color, texture and, shape of leaves. The incorporation of image processing technique into AI aids in deciding the appropriate amount of herbicide supplement to the plant based on the prediction of plant growth.
Gowrishankar Govindaraj and Arockia Selvakumar Arockia Doss
International Association of Online Engineering (IAOE)
Gait cycle plays a major role in human locomotion. Patients with neuromuscular problems are unable to walk normally. Foot drop causes difficulty in lifting the front part of the foot and affects the dorsiflexion (DF) and plantar flexion (PF) motion of the foot. Patient with foot drop must use ankle braces to achieve a normal gait. The existing ankle-foot orthosis (AFO) has its own limitations, as it does not produce adequate PF motion. To overcome this scenario, a study was conducted to analyse the two-degrees-of-freedom (DOF) motion of a robotic ankle foot orthosis (RAFO) with a spring-based series elastic actuator (SEA) and scissor actuator. The objective of this paper is to evaluate the two DOF of RAFO with two different actuators using simscape multibody. The RAFO with actuators were designed using Solidworks, and simulation was carried out using simscape multibody, to analyse the 2-DOF motion. The dynamic motion analysis was carried out using block libraries, bodies, joints, constraints, revolute joints, sensors and a proportional integral (PI) controller. From the simulation results, the total range of motion (ROM) 40° (PF angle of –25° and DF angle of 15°) is achieved by the proposed RAFO with different actuators. Further, based on the results, the input power consumption of spring-based SEA was found to be less than the scissor actuator. Similarly, torque and output power generation of the scissor actuator was found to be greater than spring-based SEA to achieve the normal human ROM. Hence, the designer can choose a hybrid actuator for foot-drop-disorder applications.
T. R. Indumathi, R. Divya, B. Senthil Kumar, and A. Selvakumar
Springer Science and Business Media LLC
T. Senthilkumar, A. Selvakumar, and B. Senthilkumar
Springer Science and Business Media LLC
A Selvakumar and Balasundaram Ananthakrishnan
Auricle Technologies, Pvt., Ltd.
The preponderance of population depends on agriculture to produce crops which would be their primary subsistence for their livelihood. So, agriculture is considered the backbone of any nation. Mango (Mangifera indica Linn), belonging to a family Anacardiaceous, is a conspicuous fruit that captivates all ages because of its meticulous taste, delicious flavor, ampleness variety, and highly lustiness. Mangoes are generally rich in minerals, vitamins, fibers, and negotiable fat. Mango plants are exposed to many micro-organisms. If these are not detected and treated in the initial developing stages, it would affect peculiar parts of the mango plant and result in loss of overall productivity. Several factors like biotic and abiotic always ensue in the decrease in the overall productivity of mango plants. Self-regulated Detection of mango plant disease is imperative, and it must be detected at the preliminary stages of the growing period of the mango plant. This paper discusses the existing methodology to classify diseases in mango plant leaves by implementing ensemble technique (Stack) which includes algorithms like Decision Tree (DT), Support vector machine (SVM), Neural Network (NN), and Logistic Regression (LR). The developmental results validate that the disease classification methodology can successfully classify a higher percentage in predicting whether mango plant leaf is healthy or diseased.
Mattapally Sai Nithin, Avesha Shaik, A Balasundaram, Kovvuri Uday Surya Deveswar Reddy, Lakshmi Sai Ram kakarla, and A Selvakumar
IEEE
Deep learning algorithms are being used to do complex tasks like extracting meaningful features, segmenting, and semantic classification of images. In recent years, these methodologies have had a substantial impact on the classification of flower types. Deep neural networks are a type of image recognition system that has been widely used in computer vision applications because of the similarities between classes and intraclass variance. Due to a greater number of flower species that are similar in shape, color, and visualization, classifying flowers is a tough task. Classification of flowers is used for different purposes, like Recognition of medicinal plants. In this paper, we implemented VGG19 and EfficientNetV2L architecture for the classification of flowers. We have fine-tuned our model compared to other methods to obtain higher accuracy. By normalizing and scaling our flower images, we underwent pre-processing. Then we input the pre-trained model of the images. we divided our flower dataset into train, test, and validation. We achieved an accuracy of 88.21 for VGG19 for 20 epochs and 96.28 for 20 epochs which provides the best accuracy than other proposed architectures in the Kaggle dataset.
The emergence of carbon nanotubes (CNT) has encouraged widespread interest among researchers with many pioneering applications achieved by exploiting the unique properties of carbon allotropes. This article is a general overview of the diversity of applications of CNT and their various forms, particularly, in the area of surface coatings. The different methods, which have been developed and practiced in the preparation, dispersion, functionalization, and metallization of CNT, are elucidated. The composite coatings have been prepared using electrochemical methods such as electroplating and electroless plating. The review presents the mechanical, electrochemical, corrosion, thermal, electrical conduction, tribological, biosensing, magnetic, and microwave absorbing properties of CNT-based composites. The incorporation of CNT substantially affects the coating performance, and the level of influence can be befittingly adjusted to suit the application needs. Various characterization studies have been conducted on these coatings, emphasizing their properties. The potential of CNT as a versatile material in catering to diverse industrial applications has placed the carbon allotrope among the elite group of materials, drawing the attention of researchers to widen their scope of utilization. The challenges, problems, and ways of the overcoming are also addressed in this review.
Balakrishnaraja Rengaraju, M Jeevanantham, S Shanmugaraja, A Selvakumar, and S Tamilselvi
IOP Publishing
K. Krishnakumar and A. Arockia Selvakumar
Defence Scientific Information and Documentation Centre
This research paper describes a technique for the enhancement of the fatigue strength of the chain link plate in the drive system of a military armoured vehicle. SAE 1541 steel link plates of chains were subjected to cyclical tensile stress due to repeated loading and un-loading conditions. The crack was getting originated from the pitch hole and growth perpendicular to the chain pulling load, due to fatigue mechanism. In general plate holes are manufactured using the conventional process. An additional novel technique called the slip ball burnishing (SBB) method is applied for improving the hole properties. The improvement is made by producing local plastic deformation, improving surface finish and compressive residual stress throughout in the pierced hole. Both the conventional process (CP) and the SBB technique have been evaluated by optical, profile, surface roughness and micro harness tests. Experimental fatigue test validations were done in both chain samples using the Johnson-Goodman method. SBB chains passed 3x106 cycles at the load of 17.61 kN and CP chains passed 3x106 cycles at the load of 13.92 kN. The conclusion was that SBB made a significant improvement of 26.51 per cent of fatigue strength compared to CP.
S. Ramakrishnan, A. Selvakumar, K. R. Nandagopalan, and R. Hariharan
AIP Publishing
The advancement in fibre-reinforced polymer (FRP) innovation have a distinct fascination in executing another sort of strands named as basalt fibre reinforced polymer (BFRP), which has the dominating of being erosion safe, strong and cost effective that deliver a predominant outcome when applied in concrete structure. Besides, the accessible codal provision and aides does not give any suggestions to the use of Basalt bars since basic investigations and significant applications are as yet restricted. The objective of our investigation was progressed by two phases. The initial phase was led by examining the properties on BFRP and STEEL bars & these properties were evaluated and compared with the codal provision. The next phase of this test included testing of eight concrete beams (4 no’s of RC beam and 4 no’s of BFRP beam) of size 1700 mm long × 150 mm wide × 250 mm profound and to examine the flexural behaviour of both BFRP and RC beam under a two -point load over a clear span of 1550 mm until failure. The outcomes of these two phases were discussed in terms of its behaviour in crack, load, flexure and the mode of failure. Additionally, the test outcomes prove that the basalt bars have a great mechanical behaviour over concrete structures and it can be set as a substitution of STEEL bars for light, temporary structures.The advancement in fibre-reinforced polymer (FRP) innovation have a distinct fascination in executing another sort of strands named as basalt fibre reinforced polymer (BFRP), which has the dominating of being erosion safe, strong and cost effective that deliver a predominant outcome when applied in concrete structure. Besides, the accessible codal provision and aides does not give any suggestions to the use of Basalt bars since basic investigations and significant applications are as yet restricted. The objective of our investigation was progressed by two phases. The initial phase was led by examining the properties on BFRP and STEEL bars & these properties were evaluated and compared with the codal provision. The next phase of this test included testing of eight concrete beams (4 no’s of RC beam and 4 no’s of BFRP beam) of size 1700 mm long × 150 mm wide × 250 mm profound and to examine the flexural behaviour of both BFRP and RC beam under a two -point load over a clear span of 1550 mm until failure. The...
S. Ramakrishnan, A. Selvakumar, K. R. Nandagopalan, and R. Vivekanandan
AIP Publishing
The headway in fiber-fortified polymer (FRP) development have an unmistakable interest in executing another kind of strands named as basalt fiber strengthened polymer (BFRP), which has the overwhelming furthest reaches of being disintegration sheltered, solid and financially savvy that convey a prevalent result when connected in solid structure. Also, the available codal arrangement and associates does not give any proposals to the utilization of BFRP bars since fundamental examinations and noteworthy applications are up ’til now limited. The target of our examination was advanced by two stages. The underlying stage was driven by inspecting the properties on BFRP and STEEL bars& these properties were assessed and contrasted and the codal arrangement. The second period of this test included testing of eight solid bars (4no’s of RC bar and 4no’s of BFRP bar) of size 1700 mm long × 150 mm wide × 250 mm significant and to inspect the shear conduct of both BFRP and RC pillar under two - point stacking over a reasonable range of 1550 mm until disappointment. The results of these two stages were talked about as far as its conduct in split, load, shear and the method of disappointment. Moreover, the test results demonstrate that the basalt bars have an extraordinary mechanical conduct over solid structures and it very well may be set as a substitution of STEEL bars for light, transitory structuresThe headway in fiber-fortified polymer (FRP) development have an unmistakable interest in executing another kind of strands named as basalt fiber strengthened polymer (BFRP), which has the overwhelming furthest reaches of being disintegration sheltered, solid and financially savvy that convey a prevalent result when connected in solid structure. Also, the available codal arrangement and associates does not give any proposals to the utilization of BFRP bars since fundamental examinations and noteworthy applications are up ’til now limited. The target of our examination was advanced by two stages. The underlying stage was driven by inspecting the properties on BFRP and STEEL bars& these properties were assessed and contrasted and the codal arrangement. The second period of this test included testing of eight solid bars (4no’s of RC bar and 4no’s of BFRP bar) of size 1700 mm long × 150 mm wide × 250 mm significant and to inspect the shear conduct of both BFRP and RC pillar under two - point stacking over a r...