Shaping Adaptive and Sustainable Smart Urban Ecosystems

The transition from smart to intelligent cities allows for the deployment and management of information and communication technologies in the urban context to be driven by holistic sustainability requirements rather than technical ones such as feasibility and fragmented, siloed operational patterns. This work proposes a multi-dimensional decision-making framework to manage a smart-intelligent city as an urban Cyber-Physical System across environmental, economic, and social sustainability pillars, metrics and their tradeoffs. A methodology based on Deep Reinforcement Learning and reward-shaping mechanisms is proposed to represent and assess sustainability pillar dependencies and their interplay. A case study on a Low-Power Wide-Area Network planning, deployment and management in a Sicilian municipality has been developed to demonstrate the effectiveness of the proposed approach in dealing with the dynamics and the non-linear dependencies of the sustainability pillars. The results thus obtained provide a blueprint for urban planners to develop sustainable, resilient, cost-effective, and environmentally friendly smart-intelligent city frameworks.