A Mobile Vehicle-Based Methodology for Dynamic Microclimate Analysis

Abstract Ultra-wideband (UWB) has broad application prospects in the field of indoor localization. In order to make up for the shortcomings of ultra-wideband that is easily affected by the environment, a positioning method based on the fusion of infrared vision and ultra-wideband is proposed. Infrared vision assists locating by identifying artificial landmarks attached to the ceiling. UWB uses an adaptive weight positioning algorithm to improve the positioning accuracy of the edge of the UWB positioning coverage area. Extended Kalman filter (EKF) is used to fuse the real-time location information of the two. Finally, the intelligent mobile vehicle-mounted platform is used to collect infrared images and UWB ranging information in the indoor environment to verify the fusion method. Experimental results show that the fusion positioning method is better than any positioning method, has the advantages of low cost, real-time performance, and robustness, and can achieve centimeter-level positioning accuracy.

Abstract Vehicle counting is one of the most basic challenges during the development and establishment of Intelligent Transport Systems (ITS). The main reason for vehicle counting is the necessity of monitoring and maintaining the transport infrastructure, preventing different kind of faults such as traffic jams. The main applied solution to this problem is video surveillance, which is presented by different kind of systems. Some of these systems use a network of static traffic cameras, expensive for establish and maintain, or mobile units, fast for redeployment, but fewer in diversity. In this paper, one particular concept of a low-cost mobile vehicle counting system is investigated, which uses an object detection method based on calculating “mass centre” of detected features of possible object. A hypothesis of improvement of the basic algorithm was formulated and a modification was proposed. In order to prove the hypothesis, both basic and modified algorithms were tested and evaluated.