Urban oods have become a constant threat to human life and property. Also, high resolution cameras in smart phones have become ubiquitous. This work involves using Computer Vision   algorithms to estimate the depth of ooding based on images taken by the general public which are geo-tagged and time-stamped. This approach will help in the implementation of effective and timely urban ood relief and management. This data can also be used to assess the effectiveness of preventive measures taken in the past and to plan remedial measures in the future. © 2017 Copyright held by the owner/author(s).
cited By ; Conference of 15th ACM International Conference on Mobile Systems, Applications, and Services, MobiSys 2017 ; Conference Date: 19 June 2017 Through 23 June 2017; Conference Code:128363
B. B. Nair and Rao, S. N., “Poster: Flood monitoring using Computer Vision”, in MobiSys 2017 - Proceedings of the 15th Annual International Conference on Mobile Systems, Applications, and Services, 2017, p. 165.