The use of unmanned aerial vehicles (UAVs) is growing rapidly across many civil application domains including realtime monitoring, providing wireless coverage, remote sensing, search and rescue, delivery of goods, security and surveillance, precision agriculture, and civil infrastructure inspection. Smart UAVs are the next big revolution in UAV technology promising to provide new opportunities in different applications, especially in civil infrastructure in terms of reduced risks and lower cost. Civil infrastructure is expected to dominate the more that $45 Billion market value of UAV usage. In this survey, we present UAV civil applications and their challenges. We also discuss current research trends and provide future insights for potential UAV uses. Furthermore, we present the key challenges for UAV civil applications, including: charging challenges, collision avoidance and swarming challenges, and networking and security related challenges. Based on our review of the recent literature, we discuss open research challenges and draw high-level insights on how these challenges might be approached.

Location-based services (LBSs) have drastically changed the way smart cities and smart buildings operate, giving a new dimension to the life of citizens. LBS have various applications ranging from power management, marketing, vehicle to everything communication to social networking, and many other applications. The concept of LBS relies on the estimation of a mobile device location either inside a city or a building. In this work, we present our three-layer collaborative LBS platform for various types of users and buildings. The first of these layers is the hardware layer consisting of the hardware used for location estimation inside smart buildings. On top of the hardware layers exists the indoor localization layer, at which we implement our indoor localization algorithms using long short-term neural networks for location estimation. Finally, the collaborative LBS system lies on top of other layers. The novelty of our approach stems from providing a complete layered architecture for LBS usage for power management. The proposed system offers collaborative features and services, that is, input to power management system that optimizes power usage in smart buildings based on user locations.

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Bridges are under various loads and environmental impacts that cause them to lose their structural integrity. A significant number of bridges in US are either structurally deficient or functionally obsolete, requiring immediate attention. Nondestructive load testing is an effective approach to measure the structural response of a bridge under various loading conditions and to determine its structural integrity. This paper presents a load-test study that evaluated the response of a prefabricated bridge with full-depth precast deck panels in Michigan. This load-test program integrates optical surveying systems, a sensor network embedded in bridge decks, and surface deflection analysis. Its major contribution lies in the exploration of an embedded sensor network that was installed initially for long-term bridge monitoring in bridge load testing. Among a number of lessons learned, it is concluded that embedded sensor network has a great potential of providing an efficient and accurate approach for obtaining real-time equivalent static stresses under varying loading scenarios.