An active product state tracking architecture in logistics sensor networks

Sensor technologies are being introduced as a means to collect the accurate and online information of products in logistics networks. Products with RFID (Radio Frequency Identification) tags can guarantee timely product location visibility. Also, additional sensors can measure location dependent attributes such as temperature and humidity. Representative product centric approaches such as EPC Network and the Dialog system make it possible to secure the item level product information automatically and fast. However, they leave room for more advanced services, especially for active product state tracking service that monitors the locations and attributes of products in a timely manner and triggers exception handling when the constraints associated with the product states are violated. Using state transition model, temporal data model, and publish/subscribe model, this paper proposes an active product state tracking system architecture which is able to track products even when they are enclosed in a box, a pallet, or a container. A simulation based experiment is provided to evaluate the performance of the proposed system.

[1]  M. Kärkkäinen,et al.  Increasing efficiency in the supply chain for short shelf life goods using RFID tagging , 2003 .

[2]  Pedro M. Reyes,et al.  Future impacts of RFID on e‐supply chains in grocery retailing , 2005 .

[3]  W. B. Lee,et al.  Design of a RFID case-based resource management system for warehouse operations , 2005, Expert Syst. Appl..

[4]  James Brusey,et al.  GLOBALLY UNIQUE PRODUCT IDENTIFIERS – REQUIREMENTS AND SOLUTIONS TO PRODUCT LIFECYCLE MANAGEMENT , 2006 .

[5]  Simson L. Garfinkel,et al.  RFID: Applications, Security, and Privacy , 2005 .

[6]  Paul H. Zipkin,et al.  The Limits of Mass Customization , 2001 .

[7]  Kary Främling,et al.  The product centric approach: a solution to supply network information management problems? , 2003, Comput. Ind..

[8]  William J. Brown,et al.  Enterprise Application Integration: A Tech Brief , 2001 .

[9]  Elgar Fleisch,et al.  RFID - The Opportunity for Logistics Service Provider , 2004 .

[10]  Fusheng Wang,et al.  Temporal Management of RFID Data , 2005, VLDB.

[11]  David S. Linthicum,et al.  Enterprise Application Integration , 1999 .

[12]  Fusheng Wang,et al.  Bridging Physical and Virtual Worlds: Complex Event Processing for RFID Data Streams , 2006, EDBT.

[13]  Anne-Marie Kermarrec,et al.  The many faces of publish/subscribe , 2003, CSUR.

[14]  Manish Bhuptani,et al.  RFID Field Guide: Deploying Radio Frequency Identification Systems , 2005 .

[15]  Diego Klabjan,et al.  Warehousing and Mining Massive RFID Data Sets , 2006, ADMA.

[16]  Jan Holmström,et al.  Agent-based model for managing composite product information , 2006, Comput. Ind..

[17]  Ralph Johnson,et al.  design patterns elements of reusable object oriented software , 2019 .

[18]  Jan Holmström,et al.  Design patterns for managing product life cycle information , 2007, CACM.

[19]  Christian S. Jensen,et al.  Temporal Entity-RelationshipModels | a Survey , 1996 .

[20]  Lionel M. Ni,et al.  An RFID-Based Distributed Control System for Mass Customization Manufacturing , 2004, ISPA.

[21]  Zhongxiao Peng,et al.  An RFID-based remote monitoring system for enterprise internal production management , 2007 .

[22]  M. Kärkkäinen,et al.  Wireless product identification: enabler for handling efficiency, customisation and information sharing , 2002 .

[23]  Damith C. Ranasinghe,et al.  EPC Network Architecture , 2008 .

[24]  C. Saygin,et al.  Adaptive inventory management using RFID data , 2007 .

[25]  Edward Fredkin,et al.  Trie memory , 1960, Commun. ACM.