Audio-Visual Low Power System for Endangered Waterbirds Monitoring

Recently, more attention is being payed to the ecological environment due rapid decline of animal species, especially birds. Wireless Multimedia Sensor Networks (WMSN) can be leveraged monitor, protect and assess changes in bird populations by periodically capturing sending images a collect station. In this paper, we propose three-tier architecture following Cloud-Fog-Edge model with an adequate placement surveillance system tasks. To address sensor network limited resources, reduce amount visual data reported compressed region interest (ROI) only target species images. Endangered birds are identified based on their calls before triggering camera. However, audio recognition likely fail ambient noise that encountered natural environment. As result, augmented our automatic song appropriate reduction technique. Thanks efficient cooperation its three tiers, proposed system, low-complexity audiovisual information processing, results better use resources while maximizing pertinent information.