AbstractThe focus of this research is in the area of Remote Condition Monitoring (RCM) for use within intermodal transport and logistics industries. For many years the intermodal transport inustry has utilised these RCM systems that have in built flaws due to the subsystems they use.
Such a study is important as the weaknesses of these subsystems have a major impact on the security and location of shipping containers. The data from these subsystems is relatively easy to
manipulate by unauthorised users and this practice has become increasingly used for illicit gain.
The research approach adopted in this thesis included an in depth literature review of current intermodal transport RCM practices and interviews with industry specialists working in this field.
This produced evidence for the construction of a conceptual framework to attempt to address the findings of this research. This conceptual framework leads to the writing of a requirement
specification. The requirement specification demonstrated the necessary operational characteristics required to build a prototype system in which the design, build and test of such a
prototype system would attempt to address the two main issues of current RCM systems.
The findings from this research provided evidence that these two main issues were found to be major contributory factors impeding accurate and reliable location and of containers and of container security. These issues are due to the use of a single flawed source of location identification and the second being security issues with the methods used in communicating remotely with monitoring devices.
The main conclusions drawn from this study are that due to the location identification unreliability and security provision provided by current RCM systems leaves these RCM systems open to unauthorised manipulation. This thesis recommends that the synthesis of currently available subsystems technologies would be a feasible approach to increase security levels and provide more accurate and reliable container location to RCM users.
|Date of Award||2016|
|Supervisor||Richard Rider (Supervisor), Qin Zhou (Supervisor) & Andrew Tickle (Supervisor)|