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Give RFID Systems an Analytical Edge
With an analytics and integration services (AIS) layer at the edge of enterprise systems, RFID solutions will become scaleable and bring real-time visibility and true automation.
Fragmented events need to be correlated. Individual events generated from RFID readers need to be correlated to make business sense out of them, as those individual events have no meaning by themselves. For example, to create an advance shipping notice (ASN) for the trading partners, the requirement is to know which cases are present in a pallet Q. If the tagged pallet Q contains 10 cases, each with its own tag, there will be 11 different RFID reads. A correlation is needed to convert 11 RFID reads to a single pallet/case relationship.
Duplicate events must be purged. For example, RFID interrogators at dock doors may read the same tag twice, 24 hours apart, and treat the reads as two distinct events. From a business perspective, however, it is a duplicate event and the second one should be ignored.
Event patterns that make business sense need to be detected. For example, if a milk pallet enters the warehouse and does not leave within 24 hours, an alert needs to be generated.
Old events must be removed. If an application is storing RFID data to detect patterns, then at some point, this information will expire and need to be purged or archived.
Applications need the ability to store event context. Applications will need to convert RFID events into business actions, and this may require storing the context in which the events were generated. At times, the same event may be needed by two different applications.
RFID data must be integrated with existing enterprise information systems. The integration of RFID data into an existing EIS is a complex process today and needs to be simplified. To achieve elusive ROI, enterprise information systems need to be informed of real-time conditions by converting RFID data into business actions.
But what should an AIS layer look like? And what do the users need?
Extracting the Most Relevant Information
AIS should have the ability to sieve out the most relevant information from filtered and consolidated RFID data sent by RFID middleware in real-time. For tracking inventory in a warehouse, when a tagged forklift carrying a new tagged pallet enters the warehouse that has a sensor at the entry door, what information about the inventory is relevant to the warehouse? Only the tag on the pallet is relevant, not the tag on the forklift.
Consider another scenario (using item-level tagging), in which Store A keeps certain brands of items. When a person carrying a bag containing a tagged item (purchased from a different retailer, Store B) visits Store A, what information is relevant to that store—any tags, or only those tagged items that truly belong to Store A? The tags from Store B need to be ignored in Store A. AIS needs to have efficient filtering mechanisms and an ability to read tags of concern, ignoring all others.
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