Assessing the Impact of Internet of Things (IoT) on Urban Multi-Modal Mobility for Optimal Routing: A Meta-Review

Intelligent transportation system is an effort to reduce traffic, travel time, thereby reducing environmental pollution. One of the solutions to reduce transportation pollution is to make the transportation system smart for users to find the optimal route, because multi-modal transportation plays an important role in passenger movement. It also manages transportation and reduces travel demand. Intelligent transportation systems have made it possible for different sectors to interact with each other. This paper aims to identify contributions of IoT factors in multi-modal mobility to find the optimal path using an umbrella review method. To achieve this, a set of studies focusing on the Internet of Things in multi-modal mobility in different fields were investigated. The sample includes 14 qualitative and 14 quantitative papers. For qualitative papers, conceptual codes were extracted. Then the significance coefficient of each variable was measured using Shannon entropy coefficient. For quantitative papers, after extracting codes and conducting inferential analysis of data using funnel plot, Egger's linear regression, publication bias and heterogeneity Q test, the effect of each of the independent variables along with the dependent variable was measured. Findings reveal that in qualitative papers, "geographical information and timetable for mobility modes" are ranked first and "the amount of electronic facilities and equipment" and "reducing route length and distance" are ranked second. In quantitative papers, the "time to reach destination", "time and volume of traffic", "number of public and private transportation stations", and "reduction in route length and distance" appeared to have a great effect on mobility.