Sujata P Pathak
@kjsce.somaiya.edu
Assistant Professor, IT
K J Somaiya College of Engineering, SVU, Vidyavihar, Mumbai
RESEARCH, TEACHING, or OTHER INTERESTS
Engineering, Computer Vision and Pattern Recognition, Renewable Energy, Sustainability and the Environment, Artificial Intelligence
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Sujata P. Pathak and Sonali A. Patil
Institute of Electrical and Electronics Engineers (IEEE)
Solar energy is a clean and renewable source of energy produced by solar panels. Solar panels deteriorate over time, resulting in generation of faults. Faults reduce the overall power generation capacity of photovoltaic (PV) plants. A variety of atmospheric and functional conditions contribute to the formation of hotspots on solar panels, indicating an increase in temperature and resulting in lower efficiency. Early detection of faults during PV module inspection and monitoring is critical for improving the efficiency, reliability, and safety of PV systems. Thermal imaging is a non-contact, non-destructive, efficient, and effective technique. With thermal image analysis, probable problem areas can be identified and fixed before actual failures or problems occur, resulting in lower costs and less human labor. In this study, the effect of pre-processing techniques on fault detection in thermal images is studied and a comparative fault detection and demarcation method is proposed. Pre-processing is one of the steps in an automated fault detection system for removing noise or artefacts from thermal images. This study investigates the impact of pre-processing techniques such as filters and histogram equalization on fault detection and demarcation accuracy. Five different types of faults, such as single cell, multicell, diode, dust/shadow, and PID hotspot are detected. For fault detection, two segmentation techniques, histogram-based color thresholding and RGB color channel-based thresholding, are applied to thermal images of solar panels. Intersection over Union (IoU) is used to determine the efficiency of fault detection and demarcation techniques. Application of filters and histogram equalization on the dataset provided increased contrast and highlighted the faulty area of the thermal image more prominently. Overall, images processed with a bilateral filter and histogram equalization performed better for fault detection and demarcation than other filters. This technique resulted in IoU values of 0.35, 0.14, 0.31, 0.54 and 0.32 for diode, dust, multicell, single cell and PID hotspots respectively.
Sujata P. Pathak and Sonali A. Patil
Springer Nature Singapore
Sujata P. Pathak, Dr.Sonali Patil, and Shailee Patel
Elsevier BV
Abhishek Parmar, Sagar Gada, Trunesh Loke, Yash Jain, Sujata Pathak, and Sonali Patil
IEEE
In the digital era where hacking and bypassing a system is easy, tampering of data is always possible leading to bad situations. Blockchain is used to store data which is near impossible to change or tamper with as it is very secure in nature. Voting as a process in any nation is an essential event and if votes get miscalculated by any external source it will be harmful. To avoid such kinds of situations and making it more comfortable blockchain technology comes in acknowledgment. This paper proposes a decentralized national e-voting system based on blockchain technology. It includes an admin panel to schedule the voting, manage candidates and declare the results. The web application will provide the users with an interface to enter their Aadhar card ID (text input) and a photo of themselves at the time of voting. The eligibility of the voter will be checked at the time they enter their Aadhar card ID. Eligible voter's phone numbers will be verified via One Time Password (OTP). After voter verification, individual voters will be considered eligible for voting. During voting, voters will be monitored through a webcam/front camera. The votes will be stored in a blockchain and any tampering would be detected easily. The address and the corresponding constituency will be checked in the backend. Voting results will be declared on a specified date and will be handled by the admin. The results will be displayed graphically with various options to choose from and will also include past results and statistics.
Divya Suvarna and Sujata Pathak
Springer International Publishing
Rugnesh Rameshram Kanojia and Sujata Pathak
IEEE
Nowadays, uses for NFC technology have been emerging day by day, the best application of NFC technology is in the contactless payment system. Similarly, due to various advantages of web application such as ease of maintenance and various user-friendly released version, the demand for new web applications supporting distinctive kinds of gadgets and intentions are persistently. Now different technologies such as Bluetooth, NFC, and BLE are being used for initiating the online payment. Considering the parameters such as cost, more reliability, and increased security, NFC technology is a best-fitted option for initiating the online vehicle toll payment system. Thus, the application of Cloud-based web application along with different IoT devices like Smartphone (having NFC feature) and NFC tag (ISO/IEC 14443) is explained in this paper. Paper the online vehicle toll payment system developed by using NFC technology is used for triggering the vehicle toll payment system supported by the web application.
Hashmeet Chadha, Satyam Mhatre, Unnati Ganatra, and Sujata Pathak
IEEE
Creating web pages is a tiresome job for experts as well as new users. In this project web pages are developed using voice commands. Voice command input from the user is converted into text commands using available speech-to-text API. Using Natural Language Processing, knowledge is extracted from these text commands and web pages are generated using intelligent system support. The proposed hardware and software for the project will be a microphone as an input device, Python programming language, voice recognition API and other required libraries for webpage development. The user is thus relieved from worrying about writing the code and can instantly build desired web pages. This voice-driven system thus saves users' time to design and build web pages.
Sujata Pathak and Arun Kulkarni
IEEE
Automatic Emotion Recognition (AER) from speech is one of the most important sub domains in affective computing. Recent technological advances have enabled human users to interact with computers in ways previously unimaginable. Beyond the confines of the keyboard and mouse, new modalities for human-computer interaction such as voice, gesture, and force-feedback are emerging. This paper explores the Linear Prediction Coefficients (LPC) of speech signal for characterizing the basic emotions from speech. The emotions used in this study are sad, anger, happy, disgust, fear, and boredom. For capturing the emotion specific information from these higher order relations, neural network (NN) is used. The decrease in the error during training phase of the NN's and the emotion recognition performance of the models, demonstrate that the excitation source component of speech contains emotion-specific information and is indeed being captured by the NN.