The unprecedented capabilities of monitoring and responding to stimuli in the physical world of wireless sensor and actuator networks (WSAN) enable these networks to provide the underpinning for several Smart City applications, such as structural health monitoring (SHM). In such applications, civil structures, endowed with wireless smart devices, are able to self-monitor and autonomously respond to situations using computational intelligence. This work presents a decentralized algorithm for detecting damage in structures by using a WSAN. As key characteristics, beyond presenting a fully decentralized (in-network) and collaborative approach for detecting damage in structures, our algorithm makes use of cooperative information fusion for calculating a damage coefficient. We conducted experiments for evaluating the algorithm in terms of its accuracy and efficient use of the constrained WSAN resources. We found that our collaborative and information fusion-based approach ensures the accuracy of our algorithm and that it can answer promptly to stimuli (1.091 s), triggering actuators. Moreover, for 100 nodes or less in the WSAN, the communication overhead of our algorithm is tolerable and the WSAN running our algorithm, operating system and protocols can last as long as 468 days.

This paper presents FraSEE, a framework whose goal is to increase the energy efficiency (EE) of smart grid applications, specifically for the Power Quality (PQ) application domain. The key idea is to use a Wireless Sensor and Actuator Network (WSAN) and decentralize the decision processes of such applications among WSAN nodes through information fusion. Experiments assessed FraSEE effectiveness in increasing the EE of a PQ application, its accuracy, i.e. correct PQ disturbance detections, considering the influence of environmental parameters in decision process, its overhead, i.e. WSAN resources consumption; and delay for performing control actions in response to decisions.

This work presents an adaptation (and enhancement) of a well-known fusion technique in order to deal with multiple applications simultaneously in a context of Shared Sensor and Actuator Networks (SSAN). SSAN allow the sensing infrastructure to be shared among multiple applications that can potentially belong to different users instead of assuming an application-specific network design. We also present simulation and tests conducted with the proposed solution on real nodes to validate our proposal.