Data format for RFID Data using a Data-on-Tag approach
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RFID tags can store more than just a tag ID. Data on an RFID tag can be updated through local processing. This is in contrast to the EPC global standard of data-on-network. In order to illustrate this concept of data-on-tag, a business scenario of a commercial laundry operation is considered. This thesis explores how data on an RFID tag can be manipulated (reading and writing) within the tag itself in the laundry bin operation of a commercial laundry. Tag manipulation in this research experiment attempts to use local processing within a tag to count and to calculate the weight of soiled linen tagged with RFID. The motivation of the thesis study is to process data at a local point and integrate it to the backend enterprise systems. Local processing avoids the need for expensive middleware, central database and network applications that are required in a data-on-network approach. Data captured from the linen and bin objects helps the laundry company with business intelligence at the enterprise level. This research experiment explores the pros and cons of a data-on-tag approach and reflects on where the future in such an approach may lie. The scope of this thesis study is to find a suitable data format for data stored in the linen and laundry bin tags. Two data formats viz CSV and XML along with compression techniques were discussed. A suitable format was chosen and a proof of concept prototype developed. The experiment conducted using the prototype examined how relevant data can be stored in the RFID tags and used in local processing without the need for a central database or network connectivity. The findings of the experiment results demonstrate sufficient proof of concept to suggest CSV data format. The experiment evaluated the accuracy of the data-on-tag approach of reading and writing data in CSV format in the tags. Issues encountered in the experiment are discussed, particularly related to writing data into the tag. The current research study opens new arenas for research study by academia in data-on-tag and in particular research on writing to tag. The research contribution aids industry and manufacturers for improved technology for writing more data into the tag accurately and efficiently. The conclusion explores the direction for future research on improving writing data on tag, using the data-on-tag approach.