Jong Heung Park

An experimental testbed for parcel handling with RFID technology

A testbed for parcel handling has been experimentally proposed to show the entire parcel handling process from pick up to delivery with emerging RFID technology. Current barcode system in postal service requires time consuming scanning process on each item that causes numerous overtime loads for field workers. RFID technology can speed up the entire parcel handling process by multi-tag recognition. Result shows successful parcel recognition at each check point and real time information system captures those recognized information. The test result also suggests some challenges must be overcome before adopting RFID in the real field

Pallet management system based on RFID in the postal logistics

In this paper, Pallet Management System (PMS) in the postal logistics based on RFID is presented. The system consists of three layers. In the first layer, tag data of pallet are captured by RFID interrogator, and these are transferred to RFID controller that it processes the data and transfers to RFID server. The second layer is to be called middleware. Finally, the data are gathered in the RFID server and used to manage the pallet.

Real-Time Diagnosis System Using Incremental Emerging Pattern Mining

Currently, as a effort to reduce a rate of death by cardiovascular diseases, a lot of researches have been studied regarding real-time diagnosis system. So, we implement a prototype which is contained of stream data processor and incremental data mining module for automatic diagnosis of cardiovascular diseases. In the prototype, (i)ECG signal data which is transported from body-attached sensor is collected and pre-processed, and (ii)diagnosis features of the bio-signal data are extracted. And the patients are automatically diagnosed using the incremental emerging pattern mining module, then (iii)the diagnosis result is provided for the doctor in charge of the patients via a web application in order to manage the medical history of each patient. So, the prototype is able to diagnose and predict patient state on real-time, automatically.