Safe Distance

Safe Distance is an app that helps monitor and promote social distancing protocols to provide a safer and healthier workplace environment. (Project ID 37)

Comment

Safe Distance (ProjectID 37)

Project by Julian Hecker, Ian Matlak, and Josh Obogbaimhe

Inspiration

Living in New York State, we see first hand the effects that COVID-19 has wrought upon workplace environments. Many people are unable to work at all, and are struggling financially.

We wanted to create a tool that will allow people to work safely, while maintaining social distance.

Using this system, it should be possible to have some return to normalcy.

Implementation 1 & 2 are both different ways of solving the same problem, to monitor and influence social distancing for a safer and healthier workplace environment.

Implementation 1 (Required Webapp and Mobile App)

What it does

Safe Distance monitors the number of people that are located within any number of customizable geofences. In the future, we will implement a feature where If there are too many people in a certain area, the mobile app will notify them to leave the area to prevent being too close to each other.

How it works

The project consists of 3 parts: The web app, mobile app, and backend.

  • Employees will activate the mobile app, which sends their live location to the Node JS/Express backend server, and stores it in the Postgresql database.
  • The Server sends the users' location data to the React frontend web app.
  • The Web App can be used to add or manage geofences, which are sent to the server and stored in the database.
  • The server monitors the users' locations and sees if they are inside a given geofence.

How we built it

  • The mobile app (works on android and ios) was built with React Native
  • The backend server and API use Node JS, Express, and PostgreSQL.
  • the web app uses DeckGL and Mapbox for maps, React, and SCSS

Implementation 2 (Required Raspi, Python, Mysql DB)

What it does

This method of SafeDistance uses a Rasp pi to collect probe requests within the antennas range. You can put this in a building to get an estimate of how many people are in a specific area.

How it works

This project consists of 1 part: Backend python script

  • It can be set on a timer to scan the area for devices nearby
  • Ones it picks up the devices it will be sent to the database
  • You can use the data to analyze average traffic in a specific area at any given time or even view live data
  • There is a second option to use a Raspberry Pi running Kali Linux to count the number of wifi-enabled devices within a certain radius and use this instead. We're working on this in another project.

How we built it

  • This back end script built with python3 using scapy library
  • The monitoring required two pieces of hardware, a NIC with monitor mode and a RaspPi

Challenges we ran into

  • Integrating the Postgres database into heroku took many hours
  • Using new map technologies was difficult with sparse documentation (DeckGL)
  • Monitoring mobile device location requires difficult background task manager
  • Getting react-native to perform tasks while the app is minimized like grab the location

Accomplishments that we're proud of

  • Creating a mobile app with background location monitoring
  • Integrating diverse technologies to work together.

What I learned

  • Make sure everyone has enough time to participate, nothing goes to plan
  • Integrating new technologies is difficult
  • How to intergrate a mobile application with a web application

What's next for Safe Distance

  • Implementing proper authentication
  • Implement a frontend page for Raspi Monitoring
  • Implement timekeeping features for clocking in/out based on location

All Repos for projects located here:

Mobile app

Web app

Raspi backend

Share this project:

Updates