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  1. null (Ed.)
    Cities offer extensive facilities to enrich the quality of life by utilizing smart devices and sensors. The Internet of Things and smart sensors connect various city services with the inhabitants. The services should be convenient and accessible to all, especially pedestrians and people with visual impairment. However, the lack of information about service locations often limits their availability and use. To this end, we developed FinderX, a Bluetooth beacon-based system to search for the nearest services and amenities. FinderX identifies the locations of nearby amenities in real-time using the signal from attached beacons. The system does not require Internet or other communication infrastructure and can function where the GPS signal is inaccessible. To demonstrate the feasibility of FinderX, we set up a testbed and evaluated the system in an urban environment. We show that FinderX has adequate usability and feasibility and reduces the time to find the amenities by 18.98\% on average. We also demonstrate that Bluetooth beacons have lower horizontal error compared to GPS in micro-positioning (where semi-indoor or surrounding infrastructure limits signal accessibility), which motivates the use of Bluetooth beacons for such applications. 
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  2. Connected Autonomous Vehicles (CAVs) have achieved significant improvements in recent years. The CAVs can share sensor data to improve autonomous driving performance and enhance road safety. CAV architecture depends on roadside edge servers for latency-sensitive applications. The roadside edge servers are equipped with high-performance embedded edge computing devices that perform calculations with low power requirements. As the number of vehicles varies over different times of the day and vehicles can request for different CAV applications, the computation requirements for roadside edge computing platform can also vary. Hence, a framework for dynamic deployment of edge computing platforms can ensure CAV applications’ performance and proper usage of the devices. In this paper, we propose R-CAV – a framework for drone-based roadside edge server deployment that provides roadside units (RSUs) based on the computation requirement. Our proof of concept implementation for object detection algorithm using Nvidia Jetson nano demonstrates the proposed framework's feasibility. We posit that the framework will enhance the intelligent transport system vision by ensuring CAV applications’ quality of service. 
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  4. null (Ed.)
    In recent years, Bluetooth beacons have been widely used in numerous application domains, including smart cities, assistive technologies, and intelligent transportation management. Researchers or developers associated with these domains frequently require diverse systems to implement or test their prototype related innovations. They need to deploy beacons for the specific environment every time; such customized systems typically cannot often be reused. Hence, the cost of implementation increases, and multiple systems generate redundant data. In this paper, we propose BeaCloud - an architecture which provides a common platform of multiple beacon-based systems. BeaCloud enables inter-system communication and allows easy and secure access to data for the system administrators. The proposed architecture presents a cost-effective model that offers reduced cost and hardware. Also, BeaCloud reduces the data redundancy by up to 40%. To demonstrate the feasibility of BeaCloud, we implemented a testbed of three testing sites and evaluated the system's performance. 
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  5. null (Ed.)
    The purpose of alerts and warnings is to provide necessary information to the public that will lead to their safety in emergencies. The nation’s alerting capabilities need to evolve and progress with the extensive use of smartphones, and newer technologies become available, especially to be more precisely targeted to sub-populations at risk. Historically, this has been a challenge as the delivery of alerts and warning messages to the public is primarily through broadcast media and signs. However, deploying such signs takes time and may not be visible to people imminent of natural hazards. Especially for road closing, marking hazards, emergency evacuation, etc., it would be beneficial to have an easy-to-deploy and automated alert/warning system that requires no line of sight. To this end, we have developed Insight – a Bluetooth beacon-based system that uses a smartphone application to sense signals from beacons marking hazard zones. The system does not require any Internet or communication infrastructure and therefore, it is resilient to breakdowns in communications during disasters. To demonstrate the feasibility of Insight, we conducted a study in an urban university campus location. The system demonstrated adequate usability and feasibility. 
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  6. null (Ed.)
    The safety of distracted pedestrians presents a significant public health challenge in the United States and worldwide. An estimated 6,704 American pedestrians died and over 200,000 pedestrians were injured in traffic crashes in 2018, according to the Centers for Disease Control and Prevention (CDC). This number is increasing annually and many researchers posit that distraction by smartphones is a primary reason for the increasing number of pedestrian injuries and deaths. One strategy to prevent pedestrian injuries and death is to use intrusive interruptions that warn distracted pedestrians directly on their smartphones. To this end, we developed StreetBit, a Bluetooth beacon-based mobile application that alerts distracted pedestrians with a visual and/or audio interruption when they are distracted by their smartphones and are approaching a potentially-dangerous traffic intersection. In this paper, we present the background, architecture, and operations of the StreetBit Application. 
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