Modeling and Building Dynamic Transportation System Based on the Internet of Things

Abstract:

Throughout our everyday lives, the importance of transport lies in facilitating people's movement or goods from one place to another. Transportation problems (TP) are not easy to fix. The choice of travel times and means of transportation has become confusing. Notably, during the periods of study and work in any city where the number of trips and congestion increases, especially at peak hours of the day. Transportation problems, therefore, cause waste of time, decreases efficiency, and dramatically adverse effects on society and citizens. Such issues include bus schedules, problems with truck routing, truck transportation problems, problems with traffic management, and so on, causing air pollution, busy highways, and unsafe highways. There is much work to address these issues. In this paper, the proposed model offers a solution to solve transportation problems using a fuzzy logic technology with traffic simulation. The proposed system, based on the Fuzzy Expert System (FES) helps find the best road, the best time of the trip, and avoids some traffic and transportation problems.

Environmental pollution is one of the most severe problems that threaten society. It affects the public health of citizens and the health of plants. Also, environmental pollution is leading to global warming. Vehicles exhaust is one of the most severe cases of environmental contamination. With the increase in the number of vehicles and the rise in congestion, it increases the exhaust and pollution resulting. In this paper, we focus on measuring the ratio of the exhaust of vehicles like CO2, CO, HC, NOX, and PMX using SUMO (Simulation of Urban Mobility). This research uses Sumo to extract real-time emission from cars over the trip on the network of routes and study the relationship between vehicle emissions and fuel consumption. Another point in this research is to measure the noise emission of the same vehicle.