Ding-Yuan Cheng

The Optimal Sampling Period of a Fingerprint Positioning Algorithm for Vehicle Speed Estimation

Using cellular floating vehicle data is a crucial technique for measuring and forecasting real-time traffic information based on anonymously sampling mobile phone positions for intelligent transportation systems (ITSs). However, a high sampling frequency generates a substantial load for ITS servers, and traffic information cannot be provided instantly when the sampling period is long. In this paper, two analytical models are proposed to analyze the optimal sampling period based on communication behaviors, traffic conditions, and two consecutive fingerprint positioning locations from the same call and estimate vehicle speed. The experimental results show that the optimal sampling period is 41.589 seconds when the average call holding time was 60 s, and the average speed error rate was only 2.87%. ITSs can provide accurate and real-time speed information under lighter loads and within the optimal sampling period. Therefore, the optimal sampling period of a fingerprint positioning algorithm is suitable for estimating speed information immediately for ITSs.

A Real-Time Pothole Detection Approach for Intelligent Transportation System

In recent years, fast economic growth and rapid technology advance have led to significant impact on the quality of traditional transport system. Intelligent transportation system (ITS), which aims to improve the transport system, has become more and more popular. Furthermore, improving the safety of traffic is an important issue of ITS, and the pothole on the road causes serious harm to drivers’ safety. Therefore, drivers’ safety may be improved with the establishment of real-time pothole detection system for sharing the pothole information. Moreover, using the mobile device to detect potholes has been more popular in recent years. This approach can detect potholes with lower cost in a comprehensive environment. This study proposes a pothole detection method based on the mobile sensing. The accelerometer data is normalized by Euler angle computation and is adopted in the pothole detection algorithm to obtain the pothole information. Moreover, the spatial interpolation method is used to reduce the location errors from global positioning system (GPS) data. In experiments, the results show that the proposed approach can precisely detect potholes without false-positives, and the higher accuracy is performed by the proposed approach. Therefore, the proposed real-time pothole detection approach can be used to improve the safety of traffic for ITS.

A Semantic Web Methodology for Situation-Aware Curative Food Service Recommendation System

Recently curative food is becoming more popular, as more people realize its benefits. Based on the theory of Chinese medicine, food itself is medicine. The Curative food which is an ideal nutritious food can help to loss weight, increase immunity and is also good for curative effects in patients. In this paper, we propose a new curative food service (CFS) recommendation system, the designed Situation-aware Curative Food Service Recommendation System (SCFSRS), which provides the cooperation web-based platform for all related mobile users (MUs) and curative food service providers (CFSPs), could strengthen the ability of CFS suggestion. SCFSRS is a five-tier system composed of the MUs, UDDI registries (UDDIRs), CFSPs, curative food services server (CFSS), and database server (DS).

Research on developing healthy-life map guiding system

Healthy-Life tourism services are the trend of the future. In this paper, we propose an effective decision support systems (DSS), the Healthy-Life Map Guiding System (HMGS), which provides the introduction and commentaries of Healthy-Life scenic spots with relevant recommendation. HMGS is combined with an automatic text summarization technology to provide summary of commentaries. Finally, HMGS provides the adaptable tourism path in 3D web geographic information system for user reaching the Healthy-Life scenic spots.

Research of Ontology and Semantic Web Apply for Building Information Model

Building Information Modeling (BIM) and Industry Foundation Classes (IFC) data model are used widely in construction to increase communication and team efficiencies while working toward a building construction management. This research presents a semantic reasoning framework using expert system development program language JESS for reasoning under specific ontology. This paper describes the structure of the proposed framework and its advantages in integrating BIM data sources. This allows the machine to understand the meaning of schema and detect error of those 3D models. This paper explores the idea of evacuation and 3D model code-checking automation.