I have always wondered about the kind of electromagnetic waves we are exposed to on a regular basis, and more specifically cell phone waves. I want to make an app that keeps track of the signal strengths of the carrier, WiFi activity etc over time and map them in a meaningful way. I am in the process of researching how to accurately quantify the exposure. I want to be able to present the data in an easily comprehendible way - " Your exposure is equivalent to _ seconds in the microwave oven". The above is a basic wireframe of what it might look like on a phone.
After we attended Don Coleman's BLE workshop, Manxue and I wanted to utilize the knowledge to explore indoor navigation. After brainstorming on the idea, we wanted to make an indoor navigation/information system for the visually impaired to guide them through a predefined indoor space. We imagined the solution to be more of 'providing important information at the right time' than an actual navigation system that puts the user on a map. We imagined a smartphone app that listens to BLE beacons placed in strategic positions to navigate a space. To elucidate, if the a user is to be guided in a subway station, the app could inform the user (through voice) if he/she is approaching a flight of stairs or a turnstile, based on multiple beacons placed strategically.
To test our concept, we made a basic app that listens to the beacons kept on a linear passage (shown in the image below). We placed three TI SensorTags separated by about 10 feet in linear fashion. We worked out the logic to figure out roughly where the phone is. It is based on listening to the signal strength from the three beacons and approximating where the user is by tracking the changing signal strengths and values. The signal strength logic is also shown in the image below (36,40 and 58 are the S/N of three beacons we used).
The video below shows the discovery of all devices within range. It uses Don Coleman's BLE plugin.
The below video demonstrates the trial app that approximates where the user is heading. The voice is for demonstration only and is yet to be incorporated into the app. Going forward, we want to try the same with Estimote beacon to test out if the signal strength is more stable. We want to improve on the algorithm to make it more reliable. Also, we would be incorporating the voice into the app.
The bigger picture is to create a platform that could be used to deploy this navigation system to various indoor spaces to help the visually impaired.