@article {98460,
	title = {EcoWatch: Region of interest-based multi-quantization resource-efficient framework for migratory bird surveillance using wireless sensor networks and environmental context awareness},
	journal = {Computers and Electrical Engineering},
	volume = {123},
	year = {2025},
	abstract = {
	Global sustainability initiatives increasingly rely on innovative technologies to safeguard biodiversity and mitigate environmental impacts. In this paper, we present EcoWatch, a novel framework that leverages Wireless Multimedia Sensor Networks (WMSNs) using LoRaWAN technology for efficient data transmission to enable real-time bird species detection and counting in their natural habitat. EcoWatch combines YOLOv8\&nbsp;You Only Look Once\&nbsp;for object detection and\&nbsp;Learning to Count Everything\&nbsp;(LTCE) for precise object counting at the base station. To address the inherent limitations of WSNs in terms of energy and bandwidth, EcoWatch incorporates a multi-level ROI-based video compression technique. Extensive evaluation demonstrates that EcoWatch significantly reduces energy consumption (up to 58.7\%) and data transmission load (by 69.8\%) compared to other methods while maintaining acceptable image quality, detection and counting accuracy. Notably, EcoWatch exhibits robust performance across seasons and adapts well to varying environmental conditions, making it a promising solution for real-world ecological monitoring applications.

},
	url = {https://doi.org/10.1016/j.compeleceng.2025.110076},
	author = {Oussama Hadji and Maimour, Moufida and Abderezzak Benyahia and Ouahab KADRI and Eric Rondeau}
}
