Publication Type:

Conference Paper


Computing, Communication and Networking Technologies (ICCCNT), 2014 International Conference on (2014)



average resolutions, Buildings, Computer vision, crowd sourcing, Emergency management, Feature extraction, feature matching, feature matching algorithm, flash floods, flood level estimation, flood monitoring, floods, Homography matrix, Image matching, Image resolution, intelligent devices, lampposts, matching feature points, network bandwidth usage, partially submerged static structures, Participatory Sensing, Sensors, Servers, SIFT, smart phones, urban flood monitoring, water drainage facilities


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.

Cite this Research Publication

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.