Radio-frequency identification (RFID) has been applied widely in applications such as supply chain visibility, pharmaceutical track and trace, etc. The standards body EPCglobal defines various interfaces in the electronic product code (EPC) network architecture to facilitate the interoperability of different applications. Logical reader is a concept defined in the application level events (ALE) specification to shield applications from knowing the physical device infrastructure. This paper proposes a new approach to the logical reader abstraction, which is defined using spatial zones and implemented by combining mobile, passive RFID with positioning technologies, such as active RFID. This hybrid approach exploits the best benefits of passive and active RFID, while maintaining compatibility with EPC standards for accessing logical readers via ALE. An evaluation of competing approaches is presented. The study shows that this spatial-zone-based design enables fine grain tracking of assets at lower infrastructure cost as compared to existing techniques (e.g., using active RFID only). The study also analyzes the accuracy of the proposed approach using numerical simulation. The results show that it outperforms a widely used chokepoint-based solution under realistic operating conditions.

It has become increasingly important to support agile organizations with easily re-configurable work environments. This paper describes an on-going work on a platform for managing behavior of intelligent environments. The platform promotes the development of futuristic workspaces that support people's work practices in an unobtrusive, context-aware, and personalized manner. The platform accommodates individual preferences and organizational policies in a way that allows rapid and impromptu customizations. There are several advantages to this, in particular, the ability to represent users' preferences about their work environments separately from the actual configurations of the physical spaces they occupy at a given time, thus supporting emerging workplace needs such as hoteling and impromptu group settings.

We describe data mining techniques designed to address the problem of selecting prospective customers from a large pool of candidates.These techniques cover a number of different scenarios, namely whether the marketing researchers have demographic information on the current customers, or the general market population, or people with propensity to become customers We also present a novel approach to the problem by exploiting the availability of a data sample from the general market population.Finally, we describe an on-line lead management and delivery system that uses the mining approach described in this paper for insurance agents to obtain qualified customer leads.