the code base for Curb-Corruption portal developed for SIH 2020.
Problem Statement PS# RK58 Software
Description: With our aim to fight against bribery, we seek Digital Solution to Combat Bribery & Justice Restoration System for better policing and improved public delivery system. Solution should (1) Provide efficient ways of public delivery system for combating bribery (2) Reporting bribery incidences to authorities. You may add value addition features to your solution.
Domain Bucket Security & Surveillance
This is a solution and an implementation of a problem statement of the Smart India Hackathon 2020. This solution focussed on combating bribery and digital policing.
Team Name: BanderSnatch
Our team developed a working web and mobile app which centered on the following aspects:
1. A reporting system which allows users to report the incidents where they were asked to pay a bribe.
2. A bribe addressing system where users can report the incidents where they had to pay a bribe.
In future, we aim to employ data visualization to help make information more open as to facilitate upward transparency. The reporting mechanism guaratees anonimity if the user opts for it, to ensure that reliable anonymous reports we have a report similarity checking mechanism. Furthermore, based on the reports we will generate an early warning system that predicts the chances of corruption happening in a department of a particular location. To automate the process we have deployed a flask based API that mines for the essential parameters for the Early Warning System based on the the report's location.
Since the prototype has not been integrated each subsection has a README file with instructions on running the Application, the project currently is divided into the following five subsections:
the following have been deployed on heroku
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Towards Digital Anti-Corruption Typology for Public Service Delivery: helped in ascertaining which digital solution to deploy in the local context of India.
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Are emerging technologies helpingwin the fight against corruption indeveloping countries?: helped in ascertaining which digital solution to deploy in the local context of India.
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Predicting Public Corruption with Neural Networks: basis of our warning system, lays out the parameters which help predict corruption levels.
Thanks goes to these wonderful people:
 Nipunika |
 Sachin Roy |
 Ayush Kumar Singh |
 Alok Anand |
 Manan Arora |
 Prakhar Garg |