Smart Tracker: Light Weight Infrastructure-less Assets Tracking solution for Ubiquitous Computing Environment
Format of Original
Institute of Electrical and Electronics Engineers (IEEE)
Fourth Annual International Conference on Mobile and Ubiquitous Systems: Networking & Services
Original Item ID
From container terminals, healthcare services, libraries to household, the role of Asset Tracking Applications has become indispensable. As the organizations grow, so do their volume of assets, soon it becomes very cumbersome to track these assets in real time and accurately prepare a financial report to avoid overbuys. Rapid development of Wireless Area Network and Radio Frequency transmitting active and passive devices like RFID tags have bolstered the deployment of Wireless Asset Tracking applications in all these disciplines. But apart from organizations where costly network infrastructures are in place to support such a reliable asset tracking task, the areas like ports, warehouses, truck stops, parks, mines, rescue spots still suffer from appropriate solutions that can cope with the adverse scenario of being devoid of infrastructure. Even high end Location Based Systems (LBS) like GPS are not scaled well in such situations. To meet these challenges, our approach presents a common platform that can locate different active and passive RF transmitting objects over the range of distances on small handheld devices. To effectively utilize the resources of the constrained handheld devices like PDA and cell phones, a light weight algorithm has been used. Our approach follows an extensible and modular architecture which offers applications from different platforms to customize and extend their functionalities. Smart Tracker has been implemented and evaluated with PDAs, RFID tags, WiFi sources for both indoor and outdoor applications.
Talukder, Nilothpal; Ahamed, Sheikh Iqbal; and Abid, Rezaul M., "Smart Tracker: Light Weight Infrastructure-less Assets Tracking solution for Ubiquitous Computing Environment" (2007). Mathematics, Statistics and Computer Science Faculty Research and Publications. 344.