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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.
Event Correlation and Analytics
AIS should have the ability to analyze information from different RFID networks, collate it and send it to relevant enterprise information systems. In order to give real-time visibility to tagged objects, RFID data needs to be aggregated and transformed into meaningful, actionable information. Current RFID systems, after doing filtering based on tag patterns, pass RFID data to existing EISs, and in turn those EISs derive meaningful information that aligns with the business process. This puts too much onus on the enterprise information systems to correlate the event patterns and make sense of the RFID data.
By doing event-pattern matching in the AIS layer, information can be presented the way an enterprise information system needs it to be, and AIS can invoke specific functions of the system. For example, if a truck starts toward a distribution center but does not reach it within a stipulated time due to an unforeseen breakdown, AIS can trigger the enterprise resource planning system's alert-generation function. For normal delivery, AIS can invoke another ERP function to register the receivables. By moving the event-pattern analysis outside the ERP, integration of RFID information becomes simple and the cost of integration is reduced.
Event aggregation is needed when a single tag read has no meaning to the application, but multiple tag reads together as one transaction make sense to the application. A warehouse management system (WMS) is interested in confirming that all cases are present on the pallet. Once a pallet enters the warehouse, tags on the pallet and cases will be reported as separate RFID reads. Correlating these individual events in the AIS layer and presenting the case-pallet relationship to the WMS is more effective and brings the cost of development down.
Event-pattern matching is needed when a combination of certain events makes sense to a business process or back-office application. For example, a store's security department does not need to be alerted every time an RFID interrogator detects an expensive camera passing through a store's exit door. But if the data is matched with other related information indicating the camera did not go through the checkout process, then AIS can alert store security that a potential theft is taking place.
AIS can provide event hierarchy (recursive event-pattern matching) when event aggregation and event-pattern matching are not adequate to generate the desired actionable business intelligence. For example, a store manager may need an alert every time a theft is detected, but the regional manager of a chain of stores in a certain area needs to be notified only when more than 10 thefts have taken place in a given month.
The AIS layer can also be used to recognize exceptions, so that under certain conditions deviating from the norm, it can send instantaneous alerts directly to the appropriate devices, systems or persons. For example, if the temperature in the medicine storage area goes above a certain limit, AIS can instantaneously send an alert to a temperature-adjusting device and to the relevant personnel as well.
Extending Real-time Visibility to EISs
The purpose of using RFID technology is to extend real-time visibility to enterprise information systems by giving them intelligent RFID feeds (sending the right information to the right processes or systems at the right time, and in the right format) so they can respond appropriately. EISs need to be alerted or notified only when a meaningful event has occurred, and not for every RFID read that happened. The definition of a meaningful event may vary across enterprises, and so a configurable rules-processing engine that does correlation and pattern-matching must be part of the AIS layer. By keeping the analysis of RFID data in an AIS layer separate from the EIS, minimal modifications to the EIS itself need to be made. For example, the application should just query the AIS layer for the real-time location of a pallet, rather than storing the last known location within itself.
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