Functionalities of Mobile Solutions for Preventing Road Traffic Health and Safety Issues in the Context of Information Management Cycle

Abstract

In the present study, researchers thoroughly analyzed the peer-reviewed literature on mobile solutions for road traffic health and safety issues with regard to their functionalities in the context of information management. A comprehensive review of papers reporting mobile solutions for road traffic health and safety was conducted using relevant eligibility criteria. Electronic sources were searched using a combination of keywords. To analyze the mobile solutions reported in the studies, the researchers deployed different aspects of the information management cycle and functionality of apps for preventing road traffic health and safety issues. Overall, 68 studies met the inclusion criteria and were included in the final analysis. A total of 72.1% of the studies reported using only the in-built sensors of smartphones in their solutions for data collection. Several processing approaches for the data were found, which can be referred to as threshold value setting, image processing, fuzzy logic, and decision tree. According to the finding, the highest percentage of processing techniques utilized in the mobile solutions belonged to threshold value setting technique (23.5%) followed by image processing technique (10.3%). The applications of mobile solutions in studies commonly include recording and providing feedback on driving behavior, real-time alerts for road conditions, accident detection, and drowsiness management. Finally, fulfilling these targets could affect humans, the physical environment, and the vehicle factors toward preventing road traffic health and safety issues. The domain researchers and developers of mobile solutions can revisit and enhance the functionalities with attention to the full cycle of information management, including data collection, data analysis, interventions, and data application in their initiatives.