A digital twin-based energy-efficient wireless multimedia sensor network for waterbirds monitoring

Wetlands play a critical role in maintaining the global climate, regulating the hydrological cycle, and protecting human health. However, they are rapidly disappearing due to human activities. Waterbirds are valuable bioindicators of wetland health, but it is challenging to monitor them effectively. Wireless Multimedia Sensor Networks (WMSNs) offer a promising technology for monitoring wetlands. Nonetheless, these networks are constrained in terms of energy, and also encounter challenges associated with large-scale deployments under natural environmental conditions. These conditions introduce harsh circumstances that may not have been anticipated during the pre -deployment testing phase. This paper proposes a Digital Twin (DT) based energyefficient WMSN monitoring system specifically tailored for waterbirds in wetlands. The system utilizes a unique approach that combines local audio identification and image compression with DT technology to optimize network performance and minimize energy consumption. To reduce unnecessary image transmissions, the system employs a real-time, low -complexity local audio identification phase before triggering image capture. A denoising step is employed to achieve highly accurate bird recognition despite surrounding noises. Each image undergoes a low -complexity compression scheme prior to transmission, further enhancing energy efficiency. To enhance the system's overall efficiency and effectiveness, DT technology is integrated to create real-time replicas of the WMSN and the monitoring application. A synergistic interaction between the two DTs enables cooperative data -making decision that ensures both QoS (Quality of Service) and QoE (Quality of Experience) requirements are met. Transmission rate control is done using a fuzzy logic decision -making technique. Realtime feedback provides rapid and accurate analysis of the current state of the WMSN, allowing for dynamic adjustments. The "what -if scenarios" feature of the implemented DTs has been effectively leveraged to find the most suitable settings for the controller. The effectiveness and performance enhancements achieved by integrating DT into our WMSN-based surveillance system are validated through comprehensive experiments in scenarios that correspond to a real -world wetland. Comparative analyses demonstrate the undeniable benefits of the DT -integrated system compared to a conventional WMSN-based surveillance setup. In particular, the results demonstrate the system's superior performance in terms of energy efficiency, real-time monitoring capabilities, and ability to handle multiple video sources.