Ant Colony Optimization Algorithm Based Vehicle Theft Prediction- revention and Recovery System Model (Aco-Vtp2rsm)
Journal Title: International Journal of Computer Science & Engineering Technology - Year 2016, Vol 7, Issue 6
Abstract
Existing vehicle security technologies are either capable of theft, prevention or recovery or both. They lack the capability to predict theft occurrence and this makes the task of theft prevention or recovery unattainable. Therefore, this research paper focuses on the development of an advance vehicle security system that is based on ant colony optimization algorithm, to enhance vehicle theft prevention, through theft perception and prevention for parked vehicles. The proposed system is capable of predicting and preventing theft, through self learning, and automatic adjustment of in-vehicle security mechanisms, such as mechanical locks level, engine immobilization, and location tracking. This is made feasible with the aid of integrated GSM technology, GPS technology, DC-DC relay, Multi-level mechanical lock, RFID technology, proximity and touch sensor. Due to the limited resources in a typical embedded controller, an ant colony algorithm for vehicle theft prediction and prevention in addition to the system architecture was designed. Analysis of the algorithm clearly showed that the system optimum performance in the search for possible theft attempt and prevention mechanism enforcement, utilizing embedded processor time not more than n2, was obtained. The analysis proved the promising capability of the system to improve vehicle theft prediction and prevention within the limited controller resources. Further work on experimentation will be done to realize the full product.
Authors and Affiliations
Ajenaghughrure Ighoyota Ben , Akazue Maureen I. , Onyekweli Charles O.
Keywords
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