ARAVINDH G
@pacolleges.org
Assistant Professor and ECE
P A COLLEGE OF ENGINEERING AND TECHNOLOGY
Scopus Publications
Scopus Publications
R. Chandrasekaran, S. Karthikkumar, A. Sheela, Pragaspathy Subramani, Aravindh. G, and Rajkumar P
IEEE
The modelling and simulation of a commercial DC rapid charging system powered by solar photovoltaic (PV) arrays are presented in this work. The active front end converter in the suggested solution uses buck-boost converters to charge the electric vehicle (EV) battery. The charging voltage is managed by the closed loop management of the buck boost converter. The simulation is carried out using the Matlab-Simulink tool, and the output results of the suggested model are compared for line and load regulations, in order to validate the proposed charging technique.
S. Pragaspathy, G. Aravindh, R. Kannan, K. Dhivya, S. Karthikkumar, and V. Karthikeyan
IEEE
There is a global wide reception for the renewable energy sectors owing to the failure phase of conventional systems in the modern society. The concern may arise because of the growing demands and obviously the setbacks created by the conventional form of power generations. Among other form of non-conventional energy sources, wind technology receives a better acceptance next to the solar photovoltaic energy generation. Battery units (BUs) are considered to be the mains of the renewable power extraction due to the unreliability of resources and the similar design structure of the BUs are unsuitable for wide applications. This particular research certainly deals about the hybrid BU technology and enhancement of its relevant characteristics to be employed for grid integration of wind energy systems respectively. The bidirectional converter study is performed, alongside grid and source side converters with appropriate control strategies and their performances are analyzed in detail. Ultra capacitor studies are imposed to suppress the power fluctuations across the DC link and allowed momentary charging of BUs based on the requirements. The state of charging (SoC) of BUs is monitored and appropriate controllers are perhaps used to manage the generation and utilization. The idea pertaining to the discussions are executed through the PSCAD simulation platform and the results are validated.
M. Arun Kumar and G. Aravindh
IEEE
The radiological characteristics of water will generally refer to the chemical, physical, biological, and radiological characteristics of water. The water quality should be strictly maintained to ensure the survival and growth of aquatic lives. Henceforth, in order to maintain the water quality, autonomous system should be implemented for monitoring Aquaculture by implemented IOT Technology is proposed in this paper. The proposed system will contain different sensors like Temperature Sensor, Water Level Sensor and the Sensor PH Sensor. Temperature, PH and Water level will play a major role in ensuring the water quality. The changes in these parameters may adversely affect the quality of the water and also the aquatic lives. GSM is used to communicate to the respective mobile phone of the user. Temperature Sensor is mainly used to detect the temperature changes and if the temperature rises above the normal value, the DC Motor will move to ON condition. The PH Sensor is used to monitor the PH value of the Soil continuously. The level of the water is monitored by using the Water level sensor and if level of the water exceeds the normal value, then the motor will be switched ON. The sensed data will be then transferred to the respective mobile phone through GSM. The GSM will send message to the Mobile when the sensors detect any abnormal value. LCD is used to display all the sensor values.
S. Jayachitra, M. Arun Kumar, G. Aravindh, R. Sangeetha, and P. Sasikala
IEEE
Seismic wave is the wave of energy that travels via the earth as a consequence of an earthquake or a volcano that occurs with low-frequency acoustic energy. By analyzing the Seismic earthquake patterns it is possible to find whether the earthquake will occur or not. In this project, the seismic data are analyzed by a Fuzzy Logic Controller. But the seismic data are affected by some unwanted artifacts. The de-noising method has the capacity to reduce the artifacts. Here the Contourlet transforms scheme gives better noise suppression in seismic images and the signal to noise ratio is improved. Further, the de-noised seismic image is segmented using Wavelet transforms for feature extraction. The extracted features can be analyzed by fuzzy Logic Controller which shows whether the seismic image is normal or abnormal. This analysis gives better results in the earthquake analysis and also in the construction of sensitive power plants.
G. Aravindh and M. Arun Kumar
IEEE
To avoid the traffic congestion and to make the efficient parking slot, it is necessary to find the parking slot within close proximity due to increased number of vehicles. In the existing system, the microcontroller was used. The main problem in the microcontroller is to register the mobile number in the central server which is located in the parking lot. The Raspberry Pi is used to overcome the problem by developing a new application in the android mobile phone. So any number of users can find the parking lot without any registration. It has vechicle detection units in the guidance of parking lot. The processor unit helps to transmits the availability of parking space from vehicle detection units based on the dectection results and android mobile for showing the available parking space in a each floor of the parking lot..
G. Aravindh and M. Arun Kumar
IEEE
The children diagnosed with hearing disabilities will lack the ability to recognize a word or sentence when it is orated. The Computer aided language learning system will remain as a boon for the children ith hearing impairment. The solution for this challenge is articulatory speech learning that has been performed by using Electropalatography(EPG) methodology, which is usually a task based language learning. The dataset combines speech and EPG of English vowels and consonants. Different statistical classifiers are investigated to recognize the vowel of electropalatography signals. The support vector machine, quadratic discriminate analysis algorithms and Linear discriminate analysis are used to classify the vowels and consonents. SVM and QDA Algorithms have been implemented to analyze the articulatory synthesis and speech synthesis, which will together decide the intonation contour of the speech utterances and tongue gestures.
M. Arun Kumar, S. Jayachithra, G. Aravindh, and M. Bhuvaneswari
IEEE
Robots will usually interact with the people directly, and hence it is very important to find an easier way for user interface. Only few robotic systems are user interfaces that possess the ability of controlling the robot by natural means, while issues such as manipulation and navigation in the environment have been focused primarily by earlier works.To promote a beneficial solution to this requirement, a system has been implemented through which the user can give commands to a wireless robot using gestures. With the help of this method, the robot can be navigated by the user by gestures using fingers, and thereby providing a way for interaction with the robotic system. By using image processing, command signals are generated from those gestures. Those command signals are then passed to the robot to navigate it in the specified direction.
A. Mohanarathinam, K.G. Dharani, R. Sangeetha, G. Aravindh, and P. Sasikala
IEEE
Artificial Intelligence [AI] and Machine Learning [ML] play a vital role in the health care industries and other such scientific applications. In continuation with Artificial Intelligence, so many researches are attracted towards the Hand Gesture Recognition (HGR). HGR is the simple method used to interact with machines. Hand gesture recognition is performed by using machine learning algorithm. It consists of two approaches, they are appearance based approach and model based approach. In appearance based method, the hand image is reconstructed by using image properties. But in model based method, different models such as volumetric, geometric etc., are used to reconstruct the image. The complications in machine learning algorithm and processing time are remaining as the major challenge in gesture recognition. The performance of HGR system is evaluated based on its accuracy. This paper presents the detailed study on various methods and algorithms used in gesture recognition.
R. Sangeetha, A. Mohanarathinam, G. Aravindh, S. Jayachitra, and M. Bhuvaneswari
IEEE
Brain tumor is the result of an abnormal growth of cells, which reproduce themselves in an uncontrolled manner. This type of tumour is diagnosed through Magnetic Resonance Imaging (MRI), which plays a significant role in segmenting the tumor region into different ways for performing surgical and medical planning assessment but the manual detection may lead to errors and it is a time consuming process. To overcome the problem, experts use various algorithms for automatic detection of the tumor region, which are based on deep learning algorithms. They are designed to train and tune millions of images within a short period of time. Further, this paper proposes different types of classification methods with a number of iterations are based on CNN architectures such as VggNet, GoogleNet and ResNet 50. For 60 iterations VggNet reports 89.33% accuracy, GoogleNet 93.45% and ResNet 50 96.50%. Finally, it is proved that ResNet 50 achieves better results than VggNet and GoogleNet with comparatively less time and better accuracy.