Qualification: 
M.Tech, B-Tech
Email: 
lekshmyvm@am.amrita.edu

V . M . Lekshmy, currently serves as Research Associate at the Amrita Center for Wireless Networks & Applications (Amrita WNA), Amritapuri. She pursued her M. Tech. in Wireless Networks and Applications, from Amrita School of Engineering, Amritapuri in 2014 and B. Tech. in Computer Science and Engineering from SNGCE College of Engineering. She is also appointed as publication coordinator of Amrita WNA from November 30, 2016 and  dissertation coordinator from 2015 till present.

Publications

Publication Type: Conference Paper

Year of Publication Publication Type Title

2016

Conference Paper

V. M. Lekshmy, Rekha, P., and Dr. Maneesha V. Ramesh, “Impact of algorithm complexity on energy utilization of wireless sensor nodes”, in 2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI), 2016.[Abstract]


Nowadays wireless sensor networks are implemented in a variety of fields to obtain real-time measurements. These networks are comprised of small, low cost devices called wireless sensor nodes (WSN). There are different types of wireless sensor nodes available in the market. Based on the requirements, wireless sensor nodes can be selected for each application. Power consumption is a major aspect in developing wireless sensor applications. In this paper, analysis of power consumption in different sensor nodes is conducted based on algorithms with different complexities. The experimental analysis results show that at a particular input current limit, Waspmote consumes 15% less power than MICAz mote in the case of O (1), 11.04% less in the case of O (n), 7.6% less in the case of O (n2), 3.9% less in case of O (log n) and 18.06% less in case of O (m+n)complex algorithms.

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2014

Conference Paper

R. Narayanan, V. M. Lekshmy, Sethuraman Rao, and Sasidhar, K., “A Novel Approach to Urban Flood Monitoring Using Computer Vision”, in Computing, Communication and Networking Technologies (ICCCNT), 2014 International Conference on, 2014.[Abstract]


Due to the high density of buildings and improper water drainage facilities, flash floods are prevalent in cities. In such scenarios, to extend timely aid, it is often required to estimate the level of flood in different parts of the affected zone. This paper presents a novel method employing participatory sensing and computer vision to estimate the flood level. The method involves the participants capturing and uploading images of the partially submerged static structures such as buildings, lampposts etc., using their smart phones or other intelligent devices. The captured images are geo-tagged and uploaded to a server. The feature matching algorithm, SIFT finds the corresponding matching feature points between the captured and a reference image at the server. The flood line is then estimated and drawn against the reference image. To optimize the network bandwidth usage, images with average resolutions are used. This method yields immediate and considerably accurate results thus helping in isolating areas that have been severely impacted for timely help. More »»
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