Audio-Visual Low Power System for Endangered Waterbirds Monitoring

Abstract

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