How we make it possible?

Our state of the art sensor fusion and machine learning algorithms combine inertial sensors (gyroscopes and accelerometers), magnetic field sensors, barometer, and GPS data to provide seamless positioning, indoors and outdoors, capturing detailed user dynamics in 3D. Our algorithms work with low cost MEMS sensors found in smartphones and wearables, providing position estimates with an accuracy of 1% of distance traveled.

Accurate to 1% of distance traveled in GPS denied conditions. Track entire activity in open sky, urban canyons and deep indoors without any position gaps.

Speed

3D attitude

3D position

Accurate roll, pitch and heading estimation in presence of high dynamics and magnetic field perturbations. Our state of the art Attitude and Heading Reference System (AHRS) provides continuous 3D attitude in all user dynamics.

Deep learning algorithms for speed modelling in different activities. Unlike other methodologies that require user specific information e.g. user's height and weight, our algorithms are user agnostic and provide speed information in all activities with no prior knowledge about users physical features. 

Context

Machine learning algorithms for user context detection including walk, run, stair climb, elevator ride, escalator ride, hand swing, hand hold and static.

Course over Ground (CoG)

User's walking direction estimation irrespective of sensors' location on the user including hand swing, hand hold, belt mount, shoulder mount and in pocket.

Rahbar in action

Start in parking

Finish at apartment door

Last mile delivery

GPS free positioning using a smart phone

• Track your packages seamlessly even when GPS is not available

• Find lost packages by bread crumbing

• Navigate to the exact address

• Navigating a multi story apartment building is quite challenging without any localization infrastructure

• Rahbar performs highly accurate 3D positioning with just a smart phone in your hand

• Climbing stairs or using an elevator, Rahbar estimates user's altitude with floor level accuracy.

Multi story apartment building

Start in parking

GPS

Rahbar

GPS signals lost

Going three stories up using stairs

Successful positioning to the apartment door

GPS degraded positioning using a smart phone

Continuous position availability

Frequent GPS outages

Seamless positioning in urban canyons

• Fill in GPS gaps

• Continuously position and track your assets

• Detailed track analytics for fitness activities

GPS

Rahbar

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