A comparative approach to the implementation of drug pedigree discovery systems
Author(s)Yu, Indy (Indy Yin)
Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
John R. Williams and Abel Sanchez.
MetadataShow full item record
As the use of RFID technology penetrates and reforms the supply-chain industry, standards are being produced at all levels of the RFID technology spectrum, ranging from hardware to software. The Electronic Product Code (EPC) standard uniquely identifies RFID-tagged products. An application that supports the usage of EPCs is an Electronic Drug Pedigree (E-Pedigree), which is a historical record that indicates the chain of custody of a particular drug product being passed from one supply-chain partner to another. In order to fully implement track-and-trace of pharmaceutical products, software systems need to be built so that pedigree documents can be effectively stored and searched. In this Thesis, two approaches that address the issue of pedigree document discovery are presented-one centralized, one decentralized. The centralized pedigree discovery service extracts metadata from pedigree documents submitted to a centralized server and uses them in a search engine, such as Google Base, to located desired documents that match client queries. The decentralized service allows pedigree documents to be stored locally by individual business owners. Each local server is attached to a Discovery Service Unit containing metadata of local pedigree documents, and these units communicate with each other to form a network. Both approaches are implemented as Web Services.
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007.Includes bibliographical references (p. 69-70).
DepartmentMassachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.; Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology
Electrical Engineering and Computer Science.