The IoT is expanding well beyond static devices, such as surveillance cameras and environment sensors. A growing number of vehicles, robots, drones and wearables are now connected, creating a rapidly expansible ecosystem with dynamic and less predictable workloads. This fluidity stretches IoT management platforms’ capabilities, which need advanced automation to deliver a seamless service in an energy-efficient manner. The first phase of this Catalyst developed a solution to follow a single “moving thing” (a drone) hopping between different edge nodes to support IoT service and network orchestration. It also applied simple techniques for energy savings. The second phase is focused on addressing this challenge at scale to support thousands of moving things which share the same infrastructure. The goal is to introduce flexible and autonomous intent-based orchestration, enabling efficient and sustainable control over large numbers of devices. The Catalyst also intends to develop and contribute a standardized API for telemetry data, enhancing interoperability across IoT ecosystems. The proposed solution will support the autonomous management of service level agreements, balancing conflicting intents and objectives in real time, together with natural language processing to set up intent conditions, thereby improving usability and configuration flexibility. Generative AI will be employed to create dynamic dashboards and monitoring reports, while AI will also identify, monitor and recommend optimizations for sustainability. The Catalyst intends to showcase the solution being employed in a real-world smart city or smart port use case. To track the impact of the project, the team will monitor API adoption, scalability benchmarks, sustainability metrics, configuration efficiency, stakeholder feedback and report generation times.