Enhanced IoT-Based End-To-End Emergency and Disaster Relief System
Qatar Mobility Innovations Center (QMIC), Qatar University, Doha P.O. Box. 210531, Qatar
SERCOM Lab, Polytechnic School of Tunisia, University of Carthage, P.O. Box 743, La Marsa 2078, Tunisia
Thomas Johann Seebeck Department of Electronics, School of Information Technology, Tallinn University of Technology, P.O. Box 10120 Tallinn, Estonia
Author to whom correspondence should be addressed.
Received: 30 June 2017 / Revised: 8 August 2017 / Accepted: 9 August 2017 / Published: 21 August 2017
In this paper, we present a new enhancement for an emergency and disaster relief system called Critical and Rescue Operations using Wearable Wireless sensors networks (CROW
). We address the reliability challenges in setting up a wireless autonomous communication system in order to offload data from the disaster area (rescuers, trapped victims, civilians, media, etc.) back to a command center. The proposed system connects deployed rescuers to extended networks and the Internet. CROW
is an end-to-end system that runs the recently-proposed Optimized Routing Approach for Critical and Emergency Networks (ORACE-Net) routing protocol. The system integrates heterogeneous wireless devices (Raspberry Pi, smart phones, sensors) and various communicating technologies (WiFi IEEE 802.11n, Bluetooth IEEE 802.15.1) to enable end-to-end network connectivity, which is monitored by a cloud Internet-of-Things platform. First, we present the CROW
generic system architecture, which is adaptable to various technologies integration at different levels (i.e., on-body, body-to-body, off-body). Second, we implement the ORACE-Net protocol on heterogeneous devices including Android-based smart phones and Linux-based Raspberry Pi devices. These devices act as on-body coordinators to collect information from on-body sensors. The collected data is then pushed to the command center thanks to multi-hop device-to-device communication. Third, the overall CROW
system performance is evaluated according to relevant metrics including end-to-end link quality estimation, throughput and end-to-end delay. As a proof-of-concept, we validate the system architecture through deployment and extracted experimental results. Finally, we highlight motion detection and links’ unavailability prevention based on the recorded data where the main factors (i.e., interference and noise) that affect the performance are analyzed.
This is an open access article distributed under the Creative Commons Attribution License
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Ben Arbia, D.; Alam, M.M.; Kadri, A.; Ben Hamida, E.; Attia, R. Enhanced IoT-Based End-To-End Emergency and Disaster Relief System. J. Sens. Actuator Netw. 2017, 6, 19.
Ben Arbia D, Alam MM, Kadri A, Ben Hamida E, Attia R. Enhanced IoT-Based End-To-End Emergency and Disaster Relief System. Journal of Sensor and Actuator Networks. 2017; 6(3):19.
Ben Arbia, Dhafer; Alam, Muhammad M.; Kadri, Abdullah; Ben Hamida, Elyes; Attia, Rabah. 2017. "Enhanced IoT-Based End-To-End Emergency and Disaster Relief System." J. Sens. Actuator Netw. 6, no. 3: 19.
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