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Special Blue

Our Mission:

We designed this to ensure that the disabled spots in front of stores, residential buildings, and jobs are reserved for those who are entitled to them. This will make sure that people with disabilities don't have to walk too far and thus, make their lives easier. We needed our project to be low cost, compact and discrete.

How it works:

The system uses a HuskyLens Camera connected to a NodeMCU to implement a Machine Learning Model that recognizes three categories: a disability tag, an empty parking space, and a full parking space. The workflow is as follows:

Empty Space Detected: No action is taken.
Occupied Space Detected: The system scans for a disability tag.
Disability Tag Found: No action is taken.
Disability Tag Not Found: An IP message is sent via WhatsApp to a designated phone number, and the incident can be managed through a web interface.

How it works

CODE:

We coded an ESP8266 microcontroller to send WhatsApp messages via the CallMeBot API based on inputs coming from the HuskyLens. It has libraries for WiFi connectivity, a web server, and HTTP's. We made a website with the device's web interface, so users can input their phone number and API key, which are then used to compose and send WhatsApp messages through the specified API endpoint when cars are parked illegally.

MECHANICAL WIRING:

We connected the camera to the Serial pins, ground, and 3.3V in the NodeMCU. We then connected a 6V battery pack into the NodeMCU so that it could work without needing a connection to the computer.

WOODWORKING:

We used woodworking to create a model of a parking lot to evaluate how our project responds to parked cars with and without disability tags.

CAD:

We wanted to connect our Camera and Microcontroller to a GoPro mount so that it can be attached to any surface and can be angled at any angle. After measuring the holes on the HuskyLens, we measured the size of the GoPro mount and from there we modeled it into fusion.