THUNDER VISION: A SMART ELECTRICITY MANAGEMENT PROJECT THAT HELPS MITIGATE REDUNDANT ELECTRICITY USAGE USING COMPUTER VISION IN CCTV CAMERAS
This is a project I built with my friend: Abhishek Jha as a part of an internship in under the AI/ML community in my university. The problem statement was that of reducing redundant electricity usage in classrooms and other office spaces in the university. For this, came to our aid, an already running project called Vision Insights that runs head-count on the CCTV cameras of the rooms. It uses a fine tuned YOLO model for the purpose of human detection. The model was trained on the images extracted from the camera footages. This runs on the RTX-4090 server situated in the makerspace of our university.
The Electricity System
So, we only needed to develop a system to remotely control the power supply to that room. To that end, I met the person in-charge of the electricity in our uni. And got to know some stuff about the MCBs of the classrooms. One thing was clear, we needed to use a device called contactor to toggle the supply on or off without even touching the MCB.
To control the contactor based on logic decisions, we needed a relay switch and we chose to use an SSR(Solid State Relay) as we found it suitable for our requirement. Further, we used a relay module to relay our signals to the SSR from the esp32.
The Remote Control
- API Key(for authorization)
- Room No.
- State: ON or OFF
In Our case, we integrated this API calling functionality in the head-count code that was already running on our RTX-4090 based server. The logic is simply- If head count != 0: Electricity supply ON, else: OFF.
And Voila! Here we had it. Within a span of 2 months of problem solving, we'd created a system to save electricity when not in use and accomplished a real-world problem too🤗🤗. Here are some clips of us testing it:





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