A Remote Monitoring and Decision-Making System for the Vehicle Rental
De Long, Jian-Jun Yi, Fei-xiang Xu, Xiao-Ming Zhu
Available Online December 2016.
- https://doi.org/10.2991/icwcsn-16.2017.20How to use a DOI?
- fault diagnosis, ontology, wireless communication, monitoring and decision making
- Vehicle rental service is being developed greatly in recent 10 years. A remote monitoring and decision-making system is proposed in this paper. This system can help the lessors to supervise their vehicles in real time. It also facilitates the customers to acquire the real time status of the rented vehicle, such as the working conditions, locations of the vehicle, costs, etc. The system consists of a data acquisition terminal and a remote monitoring and decision-making system. The data acquisition terminal is responsible for collecting and transmitting the vehicle fault information from the OBD (On-Board Diagnostics) interface and the vehicle location information from GPS module. And the remote monitoring and decision-making system integrated a fault expert system based on ontology with GIS platform, thus remote monitoring and diagnosis for vehicle can be achieved, which can provide effective suggestions when vehicle failure occurs. Ontology engineering theory is introduced in order to improve the intelligence and scalability of the expert system for fault diagnosis. Finally, some vehicle rental company is taken as an example to demonstrate the system functions. The result is proved that this system presents many advantages such as effective remote monitoring and decision making, and accurate ontology-based analysis.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - De Long AU - Jian-Jun Yi AU - Fei-xiang Xu AU - Xiao-Ming Zhu PY - 2016/12 DA - 2016/12 TI - A Remote Monitoring and Decision-Making System for the Vehicle Rental PB - Atlantis Press SP - 90 EP - 94 SN - 2352-538X UR - https://doi.org/10.2991/icwcsn-16.2017.20 DO - https://doi.org/10.2991/icwcsn-16.2017.20 ID - Long2016/12 ER -