Marc’s initial shoplifting model in his post is based on John Colapinto’s concepts of matching a pattern of customer movements in the store with their estimated patterns of shoplifting behavioral patterns.    Marc’s asks how Coral8 might address this.   We are not ready to seek a vendor solution.  We do not yet have a workable detection model.

As indicated above, I don’t think the example situation cited by John and Marc is a viable model for automated processing.    Tracking the behavior of customer’s movements, by machine, would require some very sophisticated image processing technology that would be too expensive compared to any possible loss at most retails stores.    This type of behavioral pattern recognition. in retail stores, is performed by people (security personnel), not machines, observing people.  

To develop a machine pattern recognition application to detect retail shoplifting we need to build detection models that are economically feasible.  If we are going to use a model of shoplifting pattern recognition versus anomaly detection, we need to define the objects we must track.  

In the most simple model, we have merchandise-objects.   Stores normally (physically) track merchandise-objects only at the exit/entry points of the store using some electromagnetic proximity detection technology.   In this model, the detection configuration is a combination of simple alerting with humans watching the store (”minding the store”).    This is not complex event processing.

However, if we added another object to our model, the customer-object, then we start to get more “complex,” but we have not defined “complexity” yet because we have not defined the object properties, the possible states of the objects, and the relationships between the objects that are the basis for estimated situations.

Hence, model building is constrained by available resources, simple economics and risk (cost-benefit).  If we are detecting shoplifting in Walmart the cost-benefit model for implementing an automated shoplifting detection system would be different than at a top diamond store on 5th Avenue in NYC.   Protecting loss at a weapons-grade uranium respository follows a different model than protecting loss at a handicraft shop, naturally.

Like Marc, I find models to automatically detect shoplifting interesting, so permit me to close with a general discussion of shoplifting in the context of our CEP/EP reference model.

One approach would be do determine what objects will be represented in our model.   For example, if we are going to track merchandise, we need to model the ”merchandise-object”.  If we are going to track people, we need to define the properties of this “person object.”  If we are going to represent the store layout, we need to define all these objects (store-object, table-object, shelf-object, entry-object and so forth).  The model can get “complex” quite quickly. 

Editorial Note:  An object-oriented approach greatly assists complex model building because we can benefit from OO properties such as encapsulation and polymorphism.  For example, we can define a basic “person object class” and then create superclasses of this object for “customer-object”, “manager-object”, “or criminal-object.”

Generally speaking, each object we define will require a state-model, for example, in Marc’s example of a customer moving around the store, we would need to model the possible states (customer at the entrance, at table 1, at table 2, at shelf 1, in the bathroom, at the cashier, etc.)  Indeed Marc, this is complex event processing if we have modelled multiple objects and defined object-object relationships that indicate situations of interest.   For example, customer-object at table2 where merchandise-object has the property of  ”very expensive, high risk” and then customer-object changes state to “in bathroom”.  Of course, we need more key indicators, but you get the idea.

Right now, I am typing from the Taste from Heaven Vegetarian Restaurant in Chiang Mai and my battery is running low.  The owner of this excellent restaurant also runs the Elephant Nature Park, a non-profit organization advocating and acting on behalf of the rights of the mighty elephants in Thailand.  Would be great if we could also automatically detect the situation of “elephant abuse” by poachers and other crimes against nature.   Time to get back to my delicious mushroom salad, Northeastern Thai style.

As always, thanks for reading, time for me to get back to eating!

Who doesn't remember the cone of silence from the original Get Smart TV series.  Whenever Max and the Chief had something important to discuss they would lower the cone of silence so that no one else could hear them or eavesdrop. So it is only fitting with the recent release of the Get Smart movie, Meru Networks has released a wireless cone of silence.

Meru is one of few stand alone wireless companies still hanging on out there.  So they need to be innovative to survive.  Their latest product, RF Barrier puts antennas around a physical plant to dampen and make it impossible to to listen in on wireless data exchanges.  They claim this is a first of its kind.  Thinking about it though, I don't see a big barrier to other companies having similar technology. I don't think you have to be a genius to broadcast traffic that puts out "noise" to hide legit traffic. I think the real special sauce is that this works in conjunction with Meru's other security products like wireless firewalls and secure access points.

With Motorola's recent purchase of AirDefense is having wireless IPS soon going to be table stakes in the wireless provider game?  I think it is and while Meru's RF barrier is a nice story, they are going to need to have some sort of IDS/IPS in their product line to keep up.

Who doesn't remember the cone of silence from the original Get Smart TV series.  Whenever Max and the Chief had something important to discuss they would lower the cone of silence so that no one else could hear them or eavesdrop. So it is only fitting with the recent release of the Get Smart movie, Meru Networks has released a wireless cone of silence.

Meru is one of few stand alone wireless companies still hanging on out there.  So they need to be innovative to survive.  Their latest product, RF Barrier puts antennas around a physical plant to dampen and make it impossible to to listen in on wireless data exchanges.  They claim this is a first of its kind.  Thinking about it though, I don't see a big barrier to other companies having similar technology. I don't think you have to be a genius to broadcast traffic that puts out "noise" to hide legit traffic. I think the real special sauce is that this works in conjunction with Meru's other security products like wireless firewalls and secure access points.

With Motorola's recent purchase of AirDefense is having wireless IPS soon going to be table stakes in the wireless provider game?  I think it is and while Meru's RF barrier is a nice story, they are going to need to have some sort of IDS/IPS in their product line to keep up.

Next, I suppose, is confiscating liquids at pools.

We've collectively lost our minds.

This story has a happy ending, though. A day after The New York Post published this story, Yankee Stadium reversed its ban. Now, if only the Post had that same affect on airport security.