At its core, ALE is based on SOA. It abstracts an interface of services, similar to how SQL abstracts the internal machinations of relational databases. Applications can query the engine through the ALE without concern for network protocols or device specifics.
In addition to consolidating multiple EPC read sources, this functionality brings a number of benefits. For example, the ALE makes it easy to weed out tags from a particular manufacturer or area on a warehouse floor. Time-based and delta change criteria are also useful in exception handling, such as isolating a tag that’s passed a given point once and then later regains focus.
Most importantly, ALE isolates against hardware and vendor changes, smoothes scalability problems, and resolves the complex programmatic synchronization that would otherwise be necessary to share multiple reader resources among back-end applications.
Processing the event stream
ALE isn’t the only tool needed to round out a complete RFID infrastructure, however. Making higher-level sense out of the flood of low-level RFID data is not an easy task, and not something that you can entrust to the post-mortem latency inherent in traditional BAM (business activity monitoring) software.
A solution, though, can be found in ESP (event stream processing) and CEP (complex event processing) software. Although CEP-based solutions have been around for a while, primarily in government or military applications, within the past few years viable commercial deployments have begun to appear.
When viewed as a single category, complex event stream processing mines low-level data to infer high-level patterns and trends developing in real time across multiple systems and sources. By collecting event data and infusing it with additional scope -- such as details on location, state, causality, and time reference -- these applications can rake supercharged events across complex rule sets, isolating exceptions and uncovering seemingly unrelated cause-and-effect relationships in real time.
It’s one thing to isolate an error, but it’s entirely more relevant to see the whole causal relationship leading up to that error. This is easily achievable using CEP/ESP, and the software can then direct alerts and triggers back into your enterprise systems -- ERP, manufacturing execution, or warehouse management systems, for example.
Sophisticated ESP products, such as Progress for RFID from Progress Software and StreamBase Systems’ Stream Processing Engine platform, can tap RFID and additional enterprise systems to build a more thorough event profile. For example, these solutions can easily correlate historic data, such as service-level issues or intrinsic customer value, with real-time RFID-based insight -- say, a purchase order that’s been picked but is stuck on the shop floor. Alerts from the ESP system can notify managers that an important order is about to be screwed up again and then display stock that’s available on another loading dock, allowing it to be diverted to the higher priority.