Safe map generation after a disaster, assisted by an unmanned aerial vehicle tracking system

Aljehani, Maher; Inoue, Masahiro

doi:10.1002/tee.22806

Cited by 16 publications

(8 citation statements)

References 15 publications

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“…Collected data will help rescue and relief teams to respond accordingly to ensure tasks are performed efficiently. Aljehani et al proposed drone technology together with IoT devices for enabling mobile tracking and image processing [190]. The advanced technology was used to capture an image of the disaster event.…”

Section: Collaboration Of Drone and Iot For Disaster Managementmentioning

confidence: 99%

Survey on Collaborative Smart Drones and Internet of Things for Improving Smartness of Smart Cities

et al. 2019

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Smart cities contain intelligent things which can intelligently automatically and collaboratively enhance life quality, save people's lives, and act a sustainable resource ecosystem. To achieve these advanced collaborative technologies such as drones, robotics, artificial intelligence, and Internet of Things (IoT) are required to increase the smartness of smart cities by improving the connectivity, energy efficiency, and quality of services (QoS). Therefore, collaborative drones and IoT play a vital role in supporting a lot of smartcity applications such as those involved in communication, transportation, agriculture,safety and security, disaster mitigation, environmental protection, service delivery, energy saving, e-waste reduction, weather monitoring, healthcare, etc. This paper presents a survey of the potential techniques and applications of collaborative drones and IoT which have recently been proposed in order to increase the smartness of smart cities. It provides a comprehensive overview highlighting the recent and ongoing research on collaborative drone and IoT in improving the real-time application of smart cities. This survey is different from previous ones in term of breadth, scope, and focus. In particular, we focus on the new concept of collaborative drones and IoT for improving smart-city applications. This survey attempts to show how collaborative drones and IoT improve the smartness of smart cities based on data collection, privacy and security, public safety, disaster management, energy consumption and quality of life in smart cities. It mainly focuses on the measurement of the smartness of smart cities, i.e., environmental aspects, life quality, public safety, and disaster management.

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Section: Collaboration Of Drone and Iot For Disaster Managementmentioning

confidence: 99%

Survey on Collaborative Smart Drones and Internet of Things for Improving Smartness of Smart Cities

et al. 2019

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“…Wireless Communications and Mobile Computing drone equipped with IoT devices can be used to collect data from the disaster area and its surroundings. Aljehani and Inoue [23] proposed drone technology and IoT for enabling mobile tracking and image processing. The advanced technology was used to capture an image of a disaster event.…”

Section: Related Workmentioning

confidence: 99%

Multi‐Drone Edge Intelligence and SAR Smart Wearable Devices for Emergency Communication

Alsamhi

Almalki

Al-Dois

et al. 2021

Wireless Communications and Mobile Computing

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Disasters, either manmade or natural, call for rapid and timely actions. Due to disaster, all of the communication infrastructures are destroyed, and there is no way for connection between people in disaster and others outside the disaster range. Drone technology is the critical technology for delivering communication services and guiding people and monitoring the unwanted effects of a disaster. The collaboration of advanced technologies can reduce life losses, save people’s lives, and manage the disaster crisis. The network performance of collaboration between the Internet of Things (IoT) and drone edge intelligence can help gather and process data, extend the wireless coverage area, deliver medical emergencies, provide real-time information about the emergency, and gather data from areas that are impossible for humans to reach. In this paper, we focus on the network performance for efficient collaboration of drone edge intelligence and smart wearable devices for disaster management. We focus mainly on network connectivity parameters for improving real-time data sharing between the drone edge intelligence and smart wearable devices. The relevant parameters that are considered in this study include delay, throughput, and the load from drone edge intelligence. It is further shown that network performance can have significant improvement when the abovementioned parameters are correctly optimised, and the improved performance can significantly improve the guiding/coordinating of search and rescue (SAR) teams effectively and efficiently.

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“…The UAVs significantly enhanced the quality of information delivered to the ground users and the surviving base stations in post-disaster and other unforeseen events. UAVs are suitable not only for mapping and surveying missions, but also for tracking humans after a disaster [3], [17]. In [17], a group of UAVs semi-autonomously traced the paths of human refugees and generated escape routes based on their movements, while other groups of UAVs surveyed the area.…”

Section: A Related Workmentioning

confidence: 99%

“…UAVs are suitable not only for mapping and surveying missions, but also for tracking humans after a disaster [3], [17]. In [17], a group of UAVs semi-autonomously traced the paths of human refugees and generated escape routes based on their movements, while other groups of UAVs surveyed the area. Human planners then examined these routes along with aerial image data, and created a safe map.…”

Section: A Related Workmentioning

confidence: 99%

“…The main contributions of UAV, along with their unsolved challenges such as coverage, disconnectivity, security and privacy, and quality of service, are discussed in [22]. In a previous work, the authors combined three communications techniques into a hybrid communication system [17]. A default communication module (i.e., a cellular network) was configured with two communication modules (a wireless and a radio control module), which can be activated when the cellular network is unavailable.…”

Section: B Communication System Related Workmentioning

confidence: 99%

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Performance Evaluation of Multi-UAV System in Post-Disaster Application: Validated by HITL Simulator

Aljehani

Inoue

2019

IEEE Access

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This paper proposes an evaluation of unmanned aerial vehicles (UAVs) performance in the mapping of disaster-struck areas. Sendai city in Japan, which was struck by the Tohoku earthquake/tsunami disaster in 2011, was mapped using multi-heterogeneous UAV. Normal mapping and searching missions are challenging as human resources are limited, and rescue teams are always needed to participate in disaster response mission. Mapping data and UAV performance evaluation will help rescuers to access and commence rescue operations in disaster-affected areas more effectively. Herein, flight plan designs are based on the information recorded after the disaster and on the mapping capabilities of the UAVs. The numerical and statistical results of the mapping missions were validated by executing the missions on real-time flight experiments in a simulator and analyzing the flight logs of the UAVs. After considering many factors and elements that affect the outcomes of the mapping mission, the authors provide a significant amount of useful data relevant to real UAV modules in the market. All flight plans were verified both manually and in a hardware-in-the-loop simulator developed by the authors. Most of the existing simulators support only a single UAV feature and have limited functionalities such as the ability to run different models on multiple UAVs. The simulator demonstrated the mapping and fine-tuned flight plans on an imported map of the disaster. As revealed in the experiments, the presented results and performance evaluations can effectively distribute different UAV models in post-disaster mapping missions. INDEX TERMS Path planning evaluation, UAVs, mapping missions, disaster response, searching and rescue mission, flight plan design, hardware in the loop simulator.

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Safe map generation after a disaster, assisted by an unmanned aerial vehicle tracking system

Cited by 16 publications

References 15 publications

Survey on Collaborative Smart Drones and Internet of Things for Improving Smartness of Smart Cities

Survey on Collaborative Smart Drones and Internet of Things for Improving Smartness of Smart Cities

Multi‐Drone Edge Intelligence and SAR Smart Wearable Devices for Emergency Communication

Performance Evaluation of Multi-UAV System in Post-Disaster Application: Validated by HITL Simulator

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