Recording of Data

The test was designed to give insight in how well the system works in a supermarket environment. To get the most representative demographic of the population, the chosen test persons were mostly hired by a third-party company. The test was performed using mobile devices such as self-scanners and personal phones running Android and iOS. All the devices in this test were provided by tt2.

The aim of the test was to mimic natural shopping behaviours as closely as possible. Each test-persons conducted a series of “sessions”, mock shopping rounds. They start at entrance of the store, move to, and scan various products, and then end the session at the checkout area. A product list of items randomly scattered items around the store was provided to each session.

At each product scan we measured the distance of the items’ location according to a planogram and compared it to the output of the tt2 system. To test different use-cases of the tt2 system, the provided device either showed an empty screen or a blue dot on top of map of the venue.

Sync Measurement Procedure

A sync is conducted when the test-person has walked to a predefined item and then scans the label on the shelf for that product. We measure the distance of the person relative to the predefined location of that product. A consequence of this method, there are few inaccuracies in this testing methodology which is not related to the accuracy of the system. The tt2 system measures the position of the individual holding the device. To get an accurate measurement the distance from the location of the user to the output of tt2 would need to be measured. This is not possible with our method. We measure the location, according to a planogram, of the scanned article relative the output of tt2.

● The planogram is only able to position a product on a shelf. The granularity of position is then often 90 cm, the standard width of a shelf. This means that the product is not positioned exactly as the planogram states.

● When performing the sync, the device is only within a proximity of the product. The distance between the products’ location and device can vary depending on the behaviour of the test person. In the end the system is designed to track the person walking, but the scan is performed by the device. A natural position to hold the device is a few decimetres away from the body.
● We estimate that these inaccuracies that arise due to our testing methodology is approximately 1.5m. To provide a result which is as accurate as possible without introducing any errors from the testing methodology we present a result which is 1.5m less than the recorded sync distance. If the recorded distance is less than 1.5m we set the error to 0m as this is indistinguishable from any measurement errors.

Using Sync Informationto Correct Positions

The ability to know where certain products are located can be used as an enhancing factor for our system. This allows the tt2 system to recalibrate if it detects any errors. Usually, retailers have information about their product’s location, although they often use promotional offers which make this information somewhat unreliable. Warehouses on the other hand often have complete information about scan location.
We have chosen to present our result in two different configurations, one where we have full information about the products’ placements, and one where we have none. The chosen configurations are the two extremes. The expected accuracy for a retailer is somewhere in this range, where the accuracy correlates with the correctness of the planogram.
All the results presented here are what we can achieve in real-time, which for some use cases this is the only accuracy that matters. However, there are use cases where a higher accuracy is achievable if real-time processing is not necessary. For everything related to statistics it is expected that the accuracy will be higher.

Testing Modes

We provide two different testing modes corresponding to the two use-cases that we provide.

No map mode

● The user has no map or navigation on their device.● The user tends to be more reckless with the device, putting it in their pocket, swinging with it, and putting it aside in carts, trolleys, etc.● This mode tends to be the most difficult for positioning systems.
Use cases:● Gathering statistics.● Sending location-based messages.

Wayfinding mode

● The tester is using the tt2 navigation system on their device to find their designated products.● The user tends to have their device in front of them, and not in their pocket, by the side, or elsewhere.● This mode tends to be more forgiving for positioning systems.
Use cases:● Gathering statistics.● Sending location-based messages.● Finding locations.● Route guidance (with directions relative the mobile device).