Designing security intelligent agent for petrol theft prevention

Abstract

Automotive industry has increased exponentially in recent years, and the number of car drivers has increased in the street as well, that lead to the increasing demand for using fuel stations. The increasing demand causes an increase of theft cases in the fuel stations particularly customers filling their cars and not paying for it. Although, there are several anti-petrol theft initiatives which include the use of Closed-Circuit Television Cameras (CCTV) to recognize vehicle number plates or people's faces. However, the record shows that existing methods for detecting petrol theft are less ineffective and time-consuming as it has been delayed in detecting the offenders and it is not a good measure to deter offenders as it is weak to be precise on evidence/mapping features. In this paper, Media Access Control (MAC) address detection of mobile devices used for preventing the petrol theft. Mac addresses are extracted from the customer mobile devices to develop a framework that can prevent and detect petrol theft. Also, car plate number is captured as well to develop this framework.

Keywords: Big Data Analytics, Business Intelligence, Information Security, Intelligent Agent, Internet-Of-Things (Iot), MAC Address Detection, Prevention, Privacy, Raspberry Pi