M.Tech, B-Tech

Bhavana B. Nair currently working as Research Assistant at the Amrita Center for Wireless Networks & Applications (Amrita WNA), Amritapuri. Bhavana pursued her M.Tech. in Computer Vision and Image Processing from Amrita Vishwa Vidyapeetham, Coimbatore. Her research work includes Image/ Video processing as part of Flood Evac Project at AmritaWNA. 


  • Worked as Guest Lecturer in Government Engineering College, Sreekrishnapuram, Palakkad, Kerala from July 2010 to May 2011.
  • Worked as Academic Supervisor in Atlas group of Institutions, Dubai, UAE from July 2012 to January 2013.


Publication Type: Conference Paper

Year of Publication Publication Type Title


Conference Paper

B.B. Nair and Sethuraman Rao, “Flood water depth estimation-A survey”, in 2016 IEEE International Conference on Computational Intelligence and Computing Research, ICCIC 2016, 2017.[Abstract]

Global warming induced drastic climate changes have increased the frequency of natural disasters such as flooding, worldwide. Flooding is a constant threat to humanity and reliable systems for flood monitoring and analysis need to be developed. Flood hazard assessment needs to take into account physical characteristics such as flood depth, flow velocity and the duration of flooding. This paper provides the researchers with a detailed compilation of the methods that can be used for the estimation of flood water depth. A comparative study has been done between the water depth estimation techniques based on image processing and those which does not involve image processing. The comparison is based on various attributes such as implementation methods, advantages, accuracy and cost. Image processing methods are classified based on various algorithms such as character recognition, feature extraction, region of interest (ROI), FIR filter etc. Similarly, non-image processing methods are classified based on hardware used such as sensors, level indicators, etc., and other signal based techniques. This study can be used to identify the best method for flood water depth estimation.

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