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A novel internet of things-enabled accident detection and reporting system for smart city environments
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Bhatti, Fizzah, Shah, Munam Ali, Maple, Carsten and Islam, Saif Ul (2019) A novel internet of things-enabled accident detection and reporting system for smart city environments. Sensors, 19 (9). p. 2071. doi:10.3390/s19092071
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Official URL: http://dx.doi.org/10.3390/s19092071
Abstract
Internet of Things-enabled Intelligent Transportation Systems (ITS) are gaining significant attention in academic literature and industry, and are seen as a solution to enhancing road safety in smart cities. Due to the ever increasing number of vehicles, a significant rise in the number of road accidents has been observed. Vehicles embedded with a plethora of sensors enable us to not only monitor the current situation of the vehicle and its surroundings but also facilitates the detection of incidents. Significant research, for example, has been conducted on accident rescue, particularly on the use of Information and Communication Technologies (ICT) for efficient and prompt rescue operations. The majority of such works provide sophisticated solutions that focus on reducing response times. However, such solutions can be expensive and are not available in all types of vehicles. Given this, we present a novel Internet of Things-based accident detection and reporting system for a smart city environment. The proposed approach aims to take advantage of advanced specifications of smartphones to design and develop a low-cost solution for enhanced transportation systems that is deployable in legacy vehicles. In this context, a customized Android application is developed to gather information regarding speed, gravitational force, pressure, sound, and location. The speed is a factor that is used to help improve the identification of accidents. It arises because of clear differences in environmental conditions (e.g., noise, deceleration rate) that arise in low speed collisions, versus higher speed collisions). The information acquired is further processed to detect road incidents. Furthermore, a navigation system is also developed to report the incident to the nearest hospital. The proposed approach is validated through simulations and comparison with a real data set of road accidents acquired from Road Safety Open Repository, and shows promising results in terms of accuracy.
| Item Type: | Journal Article | |||||||||
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| Divisions: | Faculty of Science > WMG (Formerly the Warwick Manufacturing Group) | |||||||||
| Journal or Publication Title: | Sensors | |||||||||
| Publisher: | MDPI | |||||||||
| ISSN: | 1424-8220 | |||||||||
| Official Date: | 3 May 2019 | |||||||||
| Dates: |
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| Date of first compliant deposit: | 6 September 2019 | |||||||||
| Volume: | 19 | |||||||||
| Number: | 9 | |||||||||
| Page Range: | p. 2071 | |||||||||
| DOI: | 10.3390/s19092071 | |||||||||
| Status: | Peer Reviewed | |||||||||
| Publication Status: | Published | |||||||||
| Access rights to Published version: | Open Access | |||||||||
| RIOXX Funder/Project Grant: |
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