- redefining indoor positioning

- redefining indoor positioning

We are launching a completely AI-based indoor positioning system.

Introducing the world's first robust indoor positioning system that operates independently from external communication tools. 

Our groundbreaking solution is powered by powerful AI-driven algorithms, meticulously trained on the world's largest proprietary dataset.

The system sets new standards for accessibility, affordability, and precise positioning...

...revolutionizing the way we navigate indoor spaces.

Why Indoor Positioning?

tt2 bringsthe blue dotindoorsindoorsindoors

We take positioning where the GPS can’t – enabling countless opportunities for countless industries.

tt2 Software is unique and scalable

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Illustration

This software can be installed on mobile phones and existing mobile computers such as scanning devices within retail and warehouses as long the have the accelerometer and gyroscope.

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Illustration

For some it’s magic. For others it’s a trailblazing innovation.For us it’s thousands of hours of programming.

After thousands of hours of cutting edge software development by our engineers .

— we’ve cracked it.

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System Performance

General Overview

The tt2 system is a revolutionary positioning system for mobile devices. Unlike all other positioning systems, we have come across, tt2 is not dependent on any external signals. The system requires that the device can provide accelerometer and gyroscope values. It can be deployed at any venue without setting up any infrastructure or doing venue-specific tuning. Together with our map-generation tool, a venue can be configured in minimal time. The only requirement to set up a new venue is to provide the tt2 system with a floorplan.
The tt2 system can be started in multiple ways. The most trivial start mode is using a fixed-point reference, such as a QR-code or a cradle storage location. Other possibilities are to start the system via external sources such as Wi-Fi-signals or GPS-signals together with a magnetometer.


The tt2 system is highly adaptable for different use cases and can be customized to suit a multitude of venues with differing requirements. We have set up a standardized test that allow us to show the overall system accuracy for tt2. Depending on the chosen setup, the expected accuracy can differ in both directions.*
The system provides a position real time, only using the computing power of the device. The delay of the positioning is of approximately 1 second. The system also provides a map which rotates so that it always “follows” physical store. This removes any ambiguities in how the map is rotated for the end user, making for an easier navigation experience. The rotation signal is instant which makes the whole user experience feel responsive.

* We have identified several factors that impact the accuracy of venues. The size of the venue impacts the accuracy where the expected accuracy is better at smaller venue. The start method can also have an impact on the expected accuracy. A start method that references the device to an exact position, such as QR/barcode-scans or cradle pickup, will give the most accurate positioning.

Methodology for Accuracy Measurements

  • 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 is 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 Information to 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.

  • Results

    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).

Accurancy with our system

    • Retailerwith tt2 Map/Wayfinding mode

    • Median dist. from edge

    • Avarage dist. from edge

    • Right Aisle %

    • Nr of visits

    • Unique users

    • Visit duration

    • Nr of scans

    • Retailerwith tt2 Map/Wayfinding mode

    • Retailerwith tt2 Map/Wayfinding mode

    • Median dist. from edge

    • Median dist. from edge

    • Avarage dist. from edge

    • Avarage dist. from edge

    • Right Aisle %

    • Right Aisle %

    • Nr of visits

    • Nr of visits

    • Unique users

    • Unique users

    • Visit duration

    • Visit duration

    • Nr of scans

    • Nr of scans

    • PS20+

    • 0,2 m

    • 0,8 m

    • 94%

    • 27

    • 13

    • 10 min

    • 207

    • Retailerwith tt2 Map/Wayfinding mode

    • PS20+

    • Median dist. from edge

    • 0,2 m

    • Avarage dist. from edge

    • 0,8 m

    • Right Aisle %

    • 94%

    • Nr of visits

    • 27

    • Unique users

    • 13

    • Visit duration

    • 10 min

    • Nr of scans

    • 207

    • Mobile

    • 0,2 m

    • 0,8 m

    • 93%

    • 28

    • 14

    • 12 min

    • 221

    • Retailerwith tt2 Map/Wayfinding mode

    • Mobile

    • Median dist. from edge

    • 0,2 m

    • Avarage dist. from edge

    • 0,8 m

    • Right Aisle %

    • 93%

    • Nr of visits

    • 28

    • Unique users

    • 14

    • Visit duration

    • 12 min

    • Nr of scans

    • 221

    • Retailer withNo map mode

    • Median dist. from edge

    • Avarage dist. from edge

    • Right Aisle %

    • Nr of visits

    • Unique users

    • Visit duration

    • Nr of scans

    • Retailer withNo map mode

    • Retailer withNo map mode

    • Median dist. from edge

    • Median dist. from edge

    • Avarage dist. from edge

    • Avarage dist. from edge

    • Right Aisle %

    • Right Aisle %

    • Nr of visits

    • Nr of visits

    • Unique users

    • Unique users

    • Visit duration

    • Visit duration

    • Nr of scans

    • Nr of scans

    • PS20+

    • 0,9 m

    • 2,7 m

    • 80%

    • 110

    • 29

    • 14 min

    • 1027

    • Retailer withNo map mode

    • PS20+

    • Median dist. from edge

    • 0,9 m

    • Avarage dist. from edge

    • 2,7 m

    • Right Aisle %

    • 80%

    • Nr of visits

    • 110

    • Unique users

    • 29

    • Visit duration

    • 14 min

    • Nr of scans

    • 1027

    • Mobile

    • 0,6 m

    • 1,9 m

    • 84%

    • 111

    • 20

    • 12 min

    • 1076

    • Retailer withNo map mode

    • Mobile

    • Median dist. from edge

    • 0,6 m

    • Avarage dist. from edge

    • 1,9 m

    • Right Aisle %

    • 84%

    • Nr of visits

    • 111

    • Unique users

    • 20

    • Visit duration

    • 12 min

    • Nr of scans

    • 1076

Illustration

- redefining indoor positioning

The tt2 system is powered by powerful AI-driven algorithms, a novel approach to using smartphone hardware components, as well as sophisticated server functionality. This enables us to create a revolutionary indoor positioning system requiring no supplementary hardware, like iBeacons, WiFi, UWB, etc

State of the art Sensor Fusion

Linking multiple hardware components together to achieve optimal data.

Adaptive positioning algorithms

Purpose-built algorithms that continuously adapt to individual movement patterns.

Deep Neural Networks

Leveraging the power of AI, and the world’s current* largest dataset of labeled indoor movement, we have developed the most powerful inertial predictive models yet.

Advanced applied mathematics

Utilizing methodologies from various domains of mathematics, from statistical modeling to optimization theory, we produce an optimal estimate of position.

Comprehensive Software Ecosystem

meaning server functionality, system. integration, multiple client platforms and indoor map solutions.

Take a look how it works

We give you the best indoor positioning system ever. The rest we leave to your imagination.

If you can give your customers or visitors an interactive guide, which they can use in their own phones, helping them discover things up to 0,5 metres accuracy
… what would you do with it?

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One solution: tt2 creates endless possibilities for using indoor positioning in a new way.

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Retail

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Airports

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Warehouses

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Malls

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Fairs

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Museums

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Railway stations

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Hospitals, Offices, Hotels...

tt2’s Value Proposition

  • Illustration

    Increased efficiency

    Route guidance in Warehouses & data on movement patterns in retail stores.

  • Illustration

    Reduced costs

    Reduce the number of employees by letting tt2 do a lot of their tasks like route guidance to product.

  • Illustration

    Location based communication

    Communicate with your users depending on their in-store location.

  • Illustration

    Drive sales

    By sending offers to users depending on their location (micro moments)

  • Illustration

    Increased customer benefits

    Search function with route guidance, smart shopping list etc.

  • Illustration

    Create newrevenue streams

    Product offers based on customers in-store location.

  • Illustration

    Increase functionality

    of existing Hardware/Scanners within Retail and Warehouses/Logistics.

Welcome to a new era in indoor positioning.
For retail, warehouses, airports, museums and areas alike.

Accurancy with our system

    • Median accuracy measured

    • No synchronisation

    • Synchronisation at scan

    • Median accuracy measured

    • Median accuracy measured

    • No synchronisation

    • No synchronisation

    • Synchronisation at scan

    • Synchronisation at scan

    • Map/Wayfinding mode

    • 0.8 m

    • 0.0 m

    • Median accuracy measured

    • Map/Wayfinding mode

    • No synchronisation

    • 0.8 m

    • Synchronisation at scan

    • 0.0 m

    • No map mode

    • 2.0 m

    • 0.3 m

    • Median accuracy measured

    • No map mode

    • No synchronisation

    • 2.0 m

    • Synchronisation at scan

    • 0.3 m

System Performance

Detailed accuracy

Methodology for Accuracy Measurements

  • 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 Information to 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).

Heading

Why Indoor Positioning?

tt2 bringsthe blue dotindoors

We take positioning where the GPS can’t – enabling countless opportunities for countless industries.

Why Indoor Positioning?

tt2 bringsthe blue dotindoors

We take positioning where the GPS can’t – enabling countless opportunities for countless industries.

tt2 Indoor Positioning

Illustration
Illustration

tt2 creates endless possibilities for using indoor positioning in a new way.

Illustration

Retail

Discover where your customers are spending their time in your store.
Discover the customer flows present in your store and how they differ depending the customer group.
Search-and-find in your scanner or “Scan&Go” app powered by tt2 real-time positioning.
Be smarter with advertising and display offers depending on the user’s location in your store.
Location based customer surveys, e.g., for customers who have visited a certain zone.

Illustration

Airports

Help your customers find their gate, a restaurant, a store, or any other point of interest with real-time navigation.
Discover where your visitors are spending their time in your airport.
Discover the customer flows present in your store and how they differ depending the customer group.

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Warehouses

Improve efficiency with real-time route optimisation and navigation for your picking orders.
Discover the bottlenecks hindering your flow in your warehouse using geospatial analytics.
Use tt2 live positioning to assign tasks to the nearest person.

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Malls

Help your customers find what they are looking for with tt2’s real-time navigation.
Discover where your customers are spending their time in your mall.
Discover the customer flows present in your mall and how they differ depending the customer group.

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Emergency services 

Help smoke divers navigate buildings with tt2’s real-time navigation.
Help tactical units track team members’ real-time position while on mission.
Use location-based communications to warn fire fighters about stairs, etc. while smoke diving.

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Fairs

Discover the most popular points of interest at your fair with geospatial analytics.
Help your visitors find what they are looking for with real-time navigation at the venue.
Give participating actors a chance to communicate with fair visitors through location-based messaging.

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Museums

Discover the most popular exhibitions at your fair with geospatial analytics.
Help your visitors find what they are looking for with real-time navigation.

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Railway stations

Help your visitors find their track, ticket offices, bathrooms, restaurants, or other points of interest with high precision real-time navigation.
Discover the most popular points of interest using geospatial analytics.

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Hospitals, offices, hotels, and other use cases… 

tt2 delivers positioning for indoor environments with no requirement of external hardware. There are endless use cases and opportunities for such a solution. 
Whatever your use case may be, we are sure that tt2 can help bring value. 

Illustration

We take positioning where the GPS can’t – enabling countless opportunities for countless industries.

Traditional Outdoor GPS positioning

The GPS or other satellite-based positioning systems, commonly used for outdoor positioning as in Google or Apple maps, require satellite signals reaching the device. When indoors, these signals typically fail to position the user sufficiently. This is where indoor positioning systems (IPSs) can help.

Unlike other IPS providers tt2 runs independently from any external signals. All you need is our SDK, a map, and a device with a gyroscope and an accelerometer (as most mobile devices have). No external hardware, no venue-specific tuning, no hassle. Welcome to the simple future of indoor positioning.

tt2 Indoor Positioning

tt2 bringsthe blue dotindoors

Accuracy with our system

    • Median accuracy measured

    • No synchronisation

    • Synchronisation at scan

    • Median accuracy measured

    • Median accuracy measured

    • No synchronisation

    • No synchronisation

    • Synchronisation at scan

    • Synchronisation at scan

    • Map/Wayfinding mode

    • 0.8 m

    • 0.0 m

    • Median accuracy measured

    • Map/Wayfinding mode

    • No synchronisation

    • 0.8 m

    • Synchronisation at scan

    • 0.0 m

    • No map mode

    • 2.0 m

    • 0.3 m

    • Median accuracy measured

    • No map mode

    • No synchronisation

    • 2.0 m

    • Synchronisation at scan

    • 0.3 m

Methodology for Accuracy Measurements

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).