M.Tech, B-Tech

Vidhya S. joined School of Engineering, Amrita Vishwa Vidyapeetham, Coimbatore, as a teaching faculty in July 2014. She received her B. Tech. degree in Computer Science and Engineering from Government Engineering College, Sreekrishnapuram, Palakkad, and M. E. degree in Computer Science and Engineering from Anna University. She currently serves as Assistant Professor in the Department of Computer Science and Engineering, School of Engineering, Coimbatore Campus. Her areas of interest include Data Structures and Algorithms, Operating System. Her areas of research include Social Computing, Graphs.


Publication Type: Journal Article

Year of Publication Title


Vidhya S, B.A. Sabarish, .Rajivkrishnan, J., and .Sachin, P., “e-vaccination:Fingerprint Based Vaccination Monitoring System”, International Journal of Pure and Applied Mathematics, vol. 118, no. 7, pp. 623-627, 2018.[Abstract]

Immunization against common childhood diseases has been an integral part of mother and child health services in India. In developing countries, current vaccination status ofinfants is recorded ina paper, which is ineffective in many ways:information which may go missing, process of looking up data is tedious. The main objective of proposed work is to use biometric traits (fingerprint) of an infant to store their vaccination schedule details,thereby automating the vaccination schedule for the infant.Biometrics traits are usedsince fingerprint of infants have great potential to accurately record immunizations and helps greatly in efficiently searching the data. The proposed method aims at developing an application which provides to alerts on a regular basis toparents and Accredited Social Health Activist (ASHA) workers based on the stored vaccination schedule information.

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R. G., Vidhya S, and S. Bharathi, D., “Survey Process Model on Palm Print and Palm Vein Using Biometric System”, International Journal of Pure and Applied Mathematics, vol. 118, pp. 1557-1563, 2018.[Abstract]

In today's world, security is the most important aspect in every field. This paper proposes a high level security system using biometrics to recognize a person. It is shown that single biometric modality recognition is not able to meet high performances. We propose a fusion of both palm vein and palm print modalities using multimodal biometric system. Instead of taking the entire image of palm, using ROI method, only a part of palm image is taken in order to overcome the hardware defects in fixing the ROI and to reduce the storage space, and to increase the security, the image is encrypted and stored. © 2018 Academic Press. All rights reserved.

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R. G., Vidhya S, and Rajasundari, T., “Matching of Dental Radiographs for Discriminating Features of Human”, International Journal of Applied Engineering Research , vol. 10, no. 7, pp. 17657-17664, 2015.


B. Dharan, Kumar, K. Akshay, Srinivasan, R., and Vidhya S, “Smartphone Based Interactive Indoor Navigation System”, Journal of Advanced Research in Dynamic and Control Systems.[Abstract]

The Smartphone based Interactive Indoor Navigation System (SIINS) is an application that is used for localization and navigation in an indoor environment, in this specific case, an academic block of Amrita Vishwa Vidyapeetham and works completely offline. The main focus of this work is to develop an efficient and effective interactive indoor localization and navigation system that operates on smartphones solely via a Wi-fi network (intranet) with a text input query system. With the advent of Global Positioning System (GPS), mobile users have navigated from one place to another with the help of the internet. Although this is very useful, it drains battery and needs many background processes to function simultaneously. SIINS is an offline application which helps locate where an end system is in an indoor environment and helps navigate from a user’s current position to other places within the environment. Such an application is needed as GPS mostly does not function efficiently in an indoor environment. Our application is mainly divided into two modules; Localization and navigation. Naive Bayes, Support Vector Machine and Random Forest algorithms are used for tracking during localization phase and dijkstra’s algorithm is used for finding the shortest path.

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