Purpose -The purpose of this paper is to provide a contemporary look at the current state-of-the-art in wireless sensor networks (WSNs) for structure health monitoring (SHM) applications and discuss the still-open research issues in this field and, hence, to make the decision-making process more effective and direct. Design/methodology/approach -This paper presents a comprehensive review of WSNs for SHM. It also introduces research challenges, opportunities, existing and potential applications. Network architecture and the state-of-the-art wireless sensor communication technologies and standards are explained. Hardware and software of the existing systems are also clarified. Findings -Existing applications and systems are presented along with their advantages and disadvantages. A comparison landscape and open research issues are also presented. Originality/value -The paper presents a comprehensive and recent review of WSN systems for SHM applications along with open research issues.

Safety and efficiency applications in vehicular networks rely on the exchange of periodic messages between vehicles. These messages contain position, speed, heading, and other vital information that makes the vehicles aware of their surroundings. The drawback of exchanging periodic cooperative messages is that they generate significant channel load. Decentralized Congestion Control (DCC) algorithms have been proposed to minimize the channel load. However, while the rationale for periodic message exchange is to improve awareness, existing DCC algorithms do not use awareness as a metric for deciding when, at what power, and at what rate the periodic messages need to be sent in order to make sure all vehicles are informed. We propose an environment-and context-aware DCC algorithm combines power and rate control in order to improve cooperative awareness by adapting to both specific propagation environments (e.g., urban intersections, open highways, suburban roads) as well as application requirements (e.g., different target cooperative awareness range). Studying various operational conditions (e.g., speed, direction, and application requirement), ECPR adjusts the transmit power of the messages in order to reach the desired awareness ratio at the target distance while at the same time controlling the channel load using an adaptive rate control algorithm. By performing extensive simulations, * Corresponding author * * M. Boban carried out this work while at NEC Laboratories Europe.

In this paper, we propose a novel distributed cooperative sensing algorithm for connected vehicles. The adaptive energy detection threshold, which is used to decide whether the channel is busy, is optimized in this work by using a computationally efficient numerical approach. The proposed optimization approach minimizes the probability of incorrect detection as a function of both the probability of false alarm and the probability of missed detection. By considering both probabilities when computing the probability of incorrect detection, to the best of the authors' knowledge the proposed approach is novel. During the energy detection process, large scale fading, multipath fading, Doppler effect, and transmission errors affecting the control messaging process are accounted in order to provide a practical solution for connected vehicles. Once the available channels have been detected, the vehicles share this information using broadcast control messages. Each vehicle evaluates the available channels by voting on the information received from one-hop neighbors, where the credibility of each neighbor is weighted during the voting process. An interdisciplinary approach referred to as entropy-based weighting is used for defining the neighbor as well as the vehicle's own credibility. The voting mechanism is switched between the proposed voting mechanism and the traditional voting approach obtained from the current-state-ofthe-art in order to maintain a balance between the computational cost/latency and robust spectrum sensing. Experimental results show that by using the proposed distributed cooperative spectrum sensing mechanism, spectrum detection error converges to zero.

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