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Automatic identification technology such as barcode and RFID can capture the IDs of physical things swiftly and accurately and allow them to be processed in computer system. This research proposes and examines the paradigm of "automatic set identification". Automatic set identification realizes the following three functionalities: "set recognition related to business transaction", "hierarchical relationship recognition of things" and "determination of IDs missing from a set". With these functionalities, the automatic set identification makes item-level identification applicable in existing transaction and warehouse applications including class-level identification. To realize these functionalities, this research works on the following two research topics: "real-space things information collection/sharing platform with automatic set identification" and "attachment of set information to physical identifier data carriers". For the first topic, this research develops an information collection/sharing platform by extending the international standard on supply chain visibility, EPCIS, and its open source implementation, fosstrak. The platform features "EPCIS adapter", a collection of Java servlets, which adds the set recognition functionalities to EPCIS. Proof-of-concept experiments and simulations with this implementation confirm that many things-related applications including class-level applications can be implemented on this platform and performance of processes related to set recognition is improved. For the second topic, this research achieves world's first method to determine identifiers of things missing from a set without any external databases and verifiers, which is an automatic set identification functionality required in offline operations. The proposed method adds redundant information calculated with a type of erasure channel error correction code to the data carriers, specifically RF tags, then verifies the integrity of a set and determine missing identifiers based on recovered identifiers. Numerical simulations and experiments with UHF RFID artifacts are done to evaluate functionality and performance of the proposal.
Keywords: Item-level identification, Information systems, EPCIS, Error correction code
Keio University, Graduate School of Media and Governance
MAUI Project
Ph.D. Dissertation
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ACADEMIC YEAR
2016 (March 23, 2017)
NAME
SATO, Yuki
TITLE
Automatic Identification of Physical and Logical Sets of Things
ABSTRACT
CONTACT
To obtain the dissertation, please contact;
SATO , Yuki ( sat3 at sfc.wide.ad.jp )