In the last decade or so, Digital Twins have emerged as a disruptive technology opening doors for digital innovation and modernization. A Digital Twin is defined as an accurate virtual model reflecting the state of a physical asset. With their futuristic applications, Digital Twins have already revolutionized several industrial sectors including product life cycle management, smart cities, healthcare and aerospace. More recently, researchers have started creating Digital Twins for natural environments. Virtual models are developed to understand, manage and protect these ecosystems which have huge potential in resisting their global decline in the face of the environmental crisis. In line with the trend, this work considers a specific Wireless Multimedia Sensor Network for waterbirds monitoring as a case study within the larger context of Digital Twins for natural environments and delivers a proof-of-concept implementation through the design and development of an associated Digital Twin system.

Waterbirds monitoring plays a pivotal role in wetland management, given that waterbirds serve as reliable indicators of wetland health. Wireless Multimedia Sensor Networks offer a promising solution for monitoring and evaluating waterbird populations in their natural habitat. Nonetheless, these networks 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. Hence, this work integrates a Digital Twin with a considered Wireless Multimedia Sensor Network acting as a replica of the system. Inorder to observe the effectiveness of the proposal through experimentation, a real-world wetland scenario is utilized. The system is validated using a specific research use-case involving the dynamic control of the image compression rate at the source nodes of the Wireless Multimedia Sensor Network. The results clearly demonstrate that the integration of Digital Twin technology brings significant value by enabling real-time optimizations and performance improvements.