- Nowadays voters vote for parties instead of individual candidates who will be responsible for solving root level problems of the voters.
- Different candidates makes different promises for different age groups and sectors of voters, and many of the times these voters are also unaware of the promises made by the candidates.
- Voters are unaware of candidates basic information and history.
An app using blockchain and machine learning can be deployed, which will match the needs of the voters with the candidates promises for the tenure.
- An interactive interface will allow the voters to fill their necessary information such as age, gender, occupation, sector of trade, expectations, requirements, etc.
- This basic information will match through the promises proposed by the candidates and will sort the candidate cards on the basis of the match, keeping the best matches in the front.
- The matched candidate card will contain the match percent and the bio of the candidate along with the verified information submitted by the candidate to the government. -These cards will also show the news the candidate was in showing the history of political activities the candidate.
- A trust parameter which will be calculated on the bases of promises kept v/s promises made previously will also be shown.
- Since the application will be using blockchain and data from the government, there won't be an inaccuracy in the data presented.
- Machine Learning can easily be used to find the matches from the submissions.
- Neural Networks can be used to predict matches.