Multi-Agent Sensor Fusion for Smart Urban Lighting: A Trust-Based Estimation Approach

This paper proposes a distributed adaptive sensor fusion architecture for an urban smart lighting system. The goal is to solve the problem of estimating the state of multi-agent systems that have three nodes: controllers, sensors, and agents. The system autonomously modulates street lamp brightness to decrease energy consumption based on vehicular traffic on designated road segments. To this end, a traffic model is proposed to estimate the number of vehicles in each segment by resorting to sensor network and state observer methodologies. At each time instant, the available information is adequately exploited by using a multi-agent reputation mechanism in turn based on distributed consensus and Perturb&Observe algorithms. A key feature of this methodology relies on its ability to identify the trustworthy sensors by evaluating an ad-hoc Quality of Service (QoS) metric. Simulations on a structured urban road network validate the effectiveness of the resulting algorithm.