@article {97384,
	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},
	number = {Part A},
	year = {2025},
	pages = {1-29},
	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 You Only Look Once for object detection and Learning to Count Everything (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://pdf.sciencedirectassets.com/271419/1-s2.0-S0045790624X00142/1-s2.0-S0045790625000199/main.pdf?X-Amz-Security-Token=IQoJb3JpZ2luX2VjEOX\%2F\%2F\%2F\%2F\%2F\%2F\%2F\%2F\%2F\%2FwEaCXVzLWVhc3QtMSJHMEUCIQCblrkGDRFRg1GVypQEKH3UyTsFstOTNdPpeosORhXunAIgGXypZhQN3sx5},
	author = {Oussama Hadji and Maimour, Moufida and Abderezzak Benyahia and Ouahab KADRI and Eric Rondeau}
}
