HangIn

Project title- HangIn Motivation behind the project (Problem we are trying to solve) A shared experience of most of the VITs population is witnessing a huge crowd in places like Library, Foodys, FC, DC or even the basketball ground at particular times of the day. This causes multiple issues like a) Last minute cancelling of plans or meetings. b) Delay in services at food joints. c) Increased unproductivity due to unavailability of seats (especially in a library or restaurants) or unavailability of a playing ground (for basketball/football etc.) Project description Our idea in gist To conduct real-time footfall analysis in the busiest areas of VIT through the database provided by external sensors and incorporate AI/ML to detect future patterns so that individuals can pre-plan their visits. Our idea aims to solve this issue in the following ways: 1) Providing real-time data to the users regarding the crowd. 2) Providing future predictions (weekly and monthly) of the footfall in all common hang-out spots of VIT.

Revenue generation Footfall data is of extreme importance to business owners since it helps them analyse whether their business models,staffing levels, products etc. require a change. We make the users of the site fill a survey to study their requirements (like timings and days at which they usually prefer to go out, locations that they visit the most, products that they are most attracted towards). Additionally, we will examine the periods of high traffic on our site to understand when the maximum number of users want to find availability of a place. This entire data analysis will be sold to owners of various eateries within the campus to generate revenue.

Future development Through our site, we aim to provide our data analytics model to various college campuses in the country. Further, we aim to reduce the hardware cost in calculation of footfall of a particular area. Tech Stack 1) Calculation of footfall:

a) IOT devices like Gazelle2,Vector 4D sensors b) IOT devices that can pick up the ping emitted by users while trying to connect to a device or router 2)Storage of data: SQLite SQLite was considered as a viable option since Django comes integrated with it. However, as the scale of our project increases in future, we plan to shift to MySQL. 2) Backend: Django framework The site’s primary focus is predictive analysis and using AI/ML to predict future patterns. Python is an excellent tool for data analysis. Hence, a web framework that supports Python language was used for the project. 3) Frontend: HTML, CSS, JavaScript, BootStrap

Instruction regarding usage of the site

The site is easy to access and does not need the user to go through the hassle of a login/signup page.
Once the site is opened, the user can visit the following sections a. Read about our site on “about us” page b. To discern various graphs and analytics regarding the footfall of the places in VIT. c. Fill the survey intended for users of the site. d. Read about the developers of the site.

Credits