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Ally – A Crowdsourced Distress Signal App

Publication Type : Conference Paper

Publisher : 2020 International Conference on Communication and Signal Processing (ICCSP), IEEE,

Source : 2020 International Conference on Communication and Signal Processing (ICCSP), IEEE, Chennai, India (2020)

Url : https://ieeexplore.ieee.org/document/9182243

Campus : Amritapuri

School : Department of Computer Science and Engineering, School of Engineering

Department : Computer Science

Year : 2020

Abstract : It is a common belief that with the advent of technology the livelihood of people in a developing community tends to get better over time. It may be true in many cases but in cases of domestic and sexual violence against women there have been no significant development. With the benefit of women, elders and basically any person who is in distress in mind and also the need for a socially centralized social network we have put forward an idea which may help curb rising crime rates by solving various issues which have been unattended by existing methodologies. Ally is a distress signal application with newer and innovative approach to solving the age old problem of rapid redressal. Existing models fail to identify the location of a person if there is no network coverage thus failing ultimately which is why we have implemented a feature to constantly track the location of a person and give the updates to guardians on an half-hourly basis. Also existing models rely on the police or the guardians to help the person in distress whereas we have taken it a step forward to crowd source help in the hour of need by sending distress signal to all nearby Ally app users within a kilometer.

Cite this Research Publication : Adithya Anand, S. Nishanth, P. Vamsi Krishna, S.R. Krishna, and Anjali T., “Ally - A Crowdsourced Distress Signal App”, in 2020 International Conference on Communication and Signal Processing (ICCSP), Chennai, India, 2020.

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