Intelligent Mobile Asset Tracking
Tracking and managing the dynamic location of mobile assets is critical for many organizations with mobile resources. Current tracking systems are costly and inefficient over wireless transmission systems where cost is based on the rate of data being sent. The intern is part of a team at UOttawa which focuses on tracking GPS-enabled mobile devices mounted on the asset by understanding the behaviour of typical traffic generated by a mobile device for reporting GPS data in various demographics. They also study Artificial Intelligence techniques for customized routing and route tracking based on the requirements of the target application. Based on this study, the intern aims to design and implement and adaptive learning-based algorithm for the data collected by the tracking software for the mobile assets. Thus, the main research goal is to develop intelligent and efficient solutions to improve existing GPS-utilized device tracking solutions and consume valuable mobile resources. As the partner organization’s line of market research is directly related to this project topic, it would enhance their range of R&D activities.