The urban population, worldwide, is growing exponentially and with it the demand for information on pollution levels, vehicle traffic, or available parking, giving rise to citizens connected to their environment. This article presents an experimental long range (LoRa) and low power consumption network, with a combination of static and mobile wireless sensors (hybrid architecture) to tune and validate concentrator placement, to obtain a large coverage in an urban environment. A mobile node has been used, carrying a gateway and various sensors. The Activation By Personalization (ABP) mode has been used, justified for urban applications requiring multicasting. This allows to compare the coverage of each static gateway, being able to make practical decisions about its location. With this methodology, it has been possible to provide service to the city of Malaga, through a single concentrator node. The information acquired is synchronized in an external database, to monitor the data in real time, being able to geolocate the dataframes through web mapping services. This work presents the development and implementation of a hybrid wireless sensor network of long range and low power, configured and tuned to achieve efficient performance in a mid-size city, and tested in experiments in a real urban environment.
Cloud robotics and advanced communications can foster a step-change in cooperative robots and hybrid wireless sensor networks (H-WSN) for demanding environments (e.g., disaster response, mining, demolition, and nuclear sites) by enabling the timely sharing of data and computational resources between robot and human teams. However, the operational complexity of such multi-agent systems requires defining effective architectures, coping with implementation details, and testing in realistic deployments. This article proposes X-IoCA, an Internet of robotic things (IoRT) and communication architecture consisting of a hybrid and heterogeneous network of wireless transceivers (H2WTN), based on LoRa and BLE technologies, and a robot operating system (ROS) network. The IoRT is connected to a feedback information system (FIS) distributed among multi-access edge computing (MEC) centers. Furthermore, we present SAR-IoCA, an implementation of the architecture for search and rescue (SAR) integrated into a 5G network. The FIS for this application consists of an SAR-FIS (including a path planner for UGVs considering risks detected by a LoRa H-WSN) and an ROS-FIS (for real-time monitoring and processing of information published throughout the ROS network). Moreover, we discuss lessons learned from using SAR-IoCA in a realistic exercise where three UGVs, a UAV, and responders collaborated to rescue victims from a tunnel accessible through rough terrain.
In the field of rescue robotics, data collection about the environment and efficient communications are fundamental for the success of search and rescue missions. Digitalization provides new ways of detecting and localizing potential victims via the wireless devices carried by the users. Nowadays, the number of personal Bluetooth low energy wearables in use (smartbands, smartwatches, earbuds...) increases constantly, being a yet-to-be-exploited personal radio frequency beacon in the case of an emergency, where the user may not be localized and unconscious. In this paper, the results of experimental tests of a Bluetooth low energy based detection system ported by terrestrial and aerial robots are provided, in order to test the feasibility of such system for the localization of the victims in unknown complex disaster areas. The results show that the tested devices can be reliably detected up to 15 meters away when using transmission power values typical of a smartphone, while being able to detect even lightly burdened devices. These results support the idea of developing an algorithm for the delimitation of areas of interest for the search and rescue groups, influencing the routes followed by the robot with the objective of exploring the detected devices area in the search of victims.
Cloud robotics and the Internet of robotic things (IoRT) can boost the performance of human-robot cooperative teams in demanding environments (e.g., disaster response, mining, demolition, and nuclear sites) by allowing timely information sharing between agents on the field (both human and robotic) and the mission control center. In previous works, we defined an Edge/Cloud-based IoRT and communications architecture for heterogeneous multi-agent systems that was applied to search and rescue missions (SAR-IoCA). In this paper, we address the integration of a remote mission control center, which performs path planning, teleoperation and mission supervision, into a ROS network. Furthermore, we present the UMA-ROS-Android app, which allows publishing smartphone sensor data, including audio and high definition images from the rear camera, and can be used by responders for requesting a robot to the control center from a geolocalized field position. The app works up to API 32 and has been shared for the ROS community. The paper offers a case study where the proposed framework was applied to a cooperative casualty evacuation mission with professional responders and an unmanned rover with two detachable stretchers in a highfidelity exercise performed in Malaga (Spain) in June 2022.
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