Blockchain-based Motion Detection in Smart Home with OpenCV and Raspberry PI
Abstract
Home security is a serious problem that must be compromised. A simple mistake like forgetting to lock the door can result in tremendous material losses. There are several ways to help the homeowner mitigate the risk. One of them is by implementing a motion detection system. This model can help the homeowner detect unknown movement in a vacant house. Besides that, the recording from the sensor can help the investigation process. However, the current model had a problem where the data were modifiable. Thus, modified data could slow down the police investigation. This study aims to improve a computer vision-based motion detection model with blockchain-based that serves as end-to-end security. With this improvement, the model can detect invalidity. Besides data protection, this model also provided Telegram access for the end-users. According to the evaluation result, the proposed model successfully captured 300 recordings with a 98% success rate. In terms of performance, the model needed up to 42% of CPU in a multiprocessor environment. The memory usage for the process needed 12.94 MB, and the data usage was 107.18 MB on average. These facts concluded that the proposed model provided data protection with a good performance aspect for embedded systems.
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