Indukala P. K., currently serves as Research Associate at the Amrita Center for Wireless Networks & Applications (Amrita WNA), Amritapuri. She pursued her M. Tech. in Computational Engineering and Networking, from Amrita School of Engineering, Coimbatore in 2013 and B. Tech. in Information Technology from College of Engineering, Thalassery (CUSAT) in 2008. She is also pursuing Ph. D. in Wireless Sensor Networks and her research work is on design and development of context aware smart sensor networks for early warning and detection of landslides, under the guidance of Dr. Seshaiah Ponnekanti.
Research Group: Machine Learning & Artificial Intelligence, Communication Systems for Extreme Environments: Landslide & Oceannet, IoT & Bigdata
Qualification
- 2008 : B. Tech in Information Technology
Cochin University of Science and Technology - 2013 : M.Tech in Computational Engineering and Networking
Amrita Vishwa Vidyapeetham, India.
Professional Appointments
- September 2014 - Present: Research Associate, Amrita Center for Wireless Networks & Applications, Amritapuri Campus
- Team Member, Amrita Wireless Sensor Network for Real-Time Landslide Monitoring Team.
- July 2015 - December 2015: Teaching Assistant for the M.Tech course, Basics of Digital Signal processing, Amrita WNA
Projects
- 2014-Present: Wireless Sensor Network for Real-Time Landslide Monitoring
Funding Agency: Ministry of Earth Sciences (MoES) - 2017-Present: IOT Framework for Modelling, Monitoring and Damage Detection of Natural and Historical Heritage Structures
Funding Agency: Department of Science & Technology (DST).
Publications
| Year of Publication | Title |
|---|---|
|
2018 |
D. Arjun, Indukala, P. K., and K. A. Unnikrishna Menon, “Border surveillance and intruder detection using wireless sensor networks: A brief survey”, in 2017 International Conference on Communication and Signal Processing (ICCSP), Chennai, India, 2018.[Abstract] Intrusion of terrorists and trespassers are adversely affecting the peace and harmony in the nation. The fatalities and disturbances caused by the latest Uri attack in Indian Army Camp show the necessity of an efficient border surveillance and intruder detection system for the effective monitoring and detecting the unauthorized movement of intruders across the national borders. Conventional border patrolling lacks an integrated multi-sensing system that coordinates various technologies for surveillance and detection of human intruder movement in the different border scenarios: flat surface movement, river/pond crossing and dry leaves movement. This paper describes the current Wireless Sensor Network (WSN) techniques related to intruder detection and border surveillance. Our future work focuses on delivering an improved multi-sensing system for detecting intrusion activities to secure the national borders. More »» |
| Year of Publication | Title |
|---|---|
|
2012 |
P. K. Indukala, Lakshmi, K., Sowmya, and Dr. Soman K. P., “Implementation of ℓ 1 magic and one bit compressed sensing based on linear programming using excel”, International Conference on Advances in Computing and Communications, ICACC 2012. IEEE, Kochi, Kerala, pp. 69-72, 2012.[Abstract] Compressed sensing helps in the reconstruction of sparse or compressible signals from small number of measurements. The sparse representation has great importance in modern signal processing. The main objective is to provide a strong understanding of the concept behind the theory of compressed sensing by using the key ideas from linear algebra. In this paper, the concept of compressed sensing is explained through an experiment formulated based on linear programming and solved using l1 magic and One bit compressed sensing methods in Excel. © 2012 IEEE. More »» |
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