An Edge Autonomous Lamp Control with Camera Feedback

Abstract

Recently IoT edge devices have become more diverse and lower cost. In addition, small low-power single-board computers' computing performance has significantly increased. These conditions make it possible to process locally without communicating to the cloud. Since the advantages of in-edge processing are security and privacy, we applied in-edge IoT to smart homes with rich private information to be secured. In in-edge processing, conventional cloud-managed abnormality monitoring and system maintenance cannot be involved. We developed a lamp control system with in-edge processing. It detects failures using camera image processing and recovers from the failure. The abnormalities of the image processing are detected by monitoring cyclic outdoor brightness change observed on windows captured with the same camera. We have developed a prototype system with Python with OpenCV and FastAPI, etc., over PHP-based lamp timer control while keeping source code size small and considering validation easiness. The camera detectors work at 10 FPS on Python with as small as 1607 total source code lines (three times of code lines against the original lamp control timer).