Design And Research Of The Dynamic Air Quality Navigation System

In recent years, "Haze" weather appeared frequently, especially in Beijing and other big cities the situation is very serious, and PM2.5 is the major component of the "Haze". "Haze" is rich in a lot of toxic and hazardous substances, seriously affecting people’s lives, so people put forward urgent demands for health traveling. With the rapid development of mobile Internet and the Crowd Sensing technology, combining mobile Internet with Crowd Sensing technology for air quality navigation has become a meaningful and challenging research.Due to less distribution point, urban fixed PM2.5 monitoring sites can not be extended to a regional air quality, through the use of PM2.5 sensors and smart phones can solve this problem. On the other hand, a few additional infrastructure based dynamic navigation has been studied to help pedestrians to choose the best route. However, the existing air quality dynamic navigation solution determine the air quality navigation route before the pedestrians’ departure. Because without considering the real-time air quality information,even when air quality of a regional in navigation route become bad, the navigation route will not change, so the navigation is not optimal.In this paper, we put forward a new type of dynamic air quality navigation scheme, which integrate crowd sensing technology with the shortest route algorithm Dijkstra, by making the pedestrian as the real-time air quality information generated and transmission nodes, it can obtain a lot of air quality information of the reference points in a certain areas, which are the important parameters for air quality navigation system. Set the weight of the edge of the network to the combination of PM2.5 and the length of road, and using the real-time air quality information transmitted in the network every fixed time slot, means the system can dynamically adjust the navigation route during the pedestrians’ walking, to achieve global optimization results.Finally, we validate our proposed scheme in the Matlab with a detailed simulation, and carry out the air quality navigation experiments in Huazhong University of Science & Technology campus map. Experimental results show that our dynamic air quality navigation scheme is obviously superior over the existing air quality navigation solution.