Design and evaluation of a decentralized urban governance system with embedded AI and blockchain-enabled IoT

The increasing complexity of smart urban environments demands governance systems capable of autonomous decision-making, secure validation, and transparent traceability. This work presents the design and functional validation of a decentralized computational architecture for urban governance, focusing exclusively on its technical feasibility without involving real-world policy implementations. The proposed system integrates Internet of Things (IoT) devices, lightweight embedded Artificial Intelligence (AI) models, and blockchain-based smart contracts to enable automated, auditable, and fault-tolerant decision-making. The evaluation is carried out in a controlled environment equipped with Raspberry Pi boards, physical sensors, and actuators representing key urban infrastructure. Governance actions–such as adaptive lighting and traffic signal control–are inferred locally through embedded AI, validated through blockchain smart contracts, and executed only when validation logic is satisfied. Five operational scenarios of increasing complexity were conducted. The system consistently achieves response times between 230–360 ms, AI inference accuracy from 95% to 81%, and blockchain validation rates above 83%. It also recovers from hardware or connectivity failures in under 10 s. This study confirms the technical viability of distributed governance architectures powered by embedded intelligence and decentralized validation mechanisms.