Video Camera and Sensor Status Monitoring System in IoT Environments

Recent progress in Ambient Intelligence (AmI) technology leads to many proposals of sensing systems in the physical, informational, and social worlds. Such systems focus primarily on the sensed data retrieval, including advanced cases of Internet of Things (IoT) sensors and video capture. Operation of a sensor is subject to faults, anomalies, and outliers. In this work-in-progress paper, we consider the problem of tracking the operation of a video camera or environment sensor to recognize deviations from the expected function. The recognition is based on neural network and context analysis. We implemented a module that makes a sensor smart in terms of operation status recognition and its self-understanding. Our demo shows the applicability of the module in IoT monitoring systems.