IoT
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Raspberry Pi
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Table of Contents
Theft detector project objective is to track the surveillance area and alert the user if any movement is detected. The alerting system includes MMS and calling the user done with twilio. User can update multiple numbers to receive mms and call. Movement detection and image processing are done with OpenCV. Object detection is one of the main features that detect what object is in the image done with yolo deep learning model. Http server used to transfer images. Suspected scenes are captured in image format and store the image locally and in the cloud by firebase, accessed globally. MIT licenses this project. If you like this project, give a star and follow me.
Device: RaspberryPi & Laptop/PC
OS: Windows/Linux/Mac
Network: 3G or Above 3G
Step 1: Download Sender_Camera.py file in system and Receiver_System.py file in raspberry pi.
Step 2: Activate http server through system terminal.
Step 3: Run Receiver_System.py and then Sender_Camera.py.
Usage of this project is to track the theft under the surveillance area and alert the user through call and mms. User can update multiple numbers to receive mms and call. Suspected scenes are captured in image format and stored securely in firebase, So you can access globally.
View Screenshots here.
Distributed under the MIT License. See LICENSE for more information.
OS: Raspbian
Model: Raspberry Pi Zero WH
Ram: 512mb
Disk: SD 32gb
OS: Garuda
Model: Acer Aspire 5 A515-51G
Processor: Intel i5 7th gen
Ram: DDR4 8gb
Disk: HDD 100gb
Akash.A,
Computer Science Engineer,
[email protected],
8608550403,
Chennai.
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