Which underlying technology does Mist use to calculate BLE location?

Juniper Mist's patented virtual Bluetooth LE (vBLE) technology uses a sophisticated approach for location calculation. Each Mist Access Point contains a dynamic 16-element vBLE antenna array. The Mist AI engine in the cloud processes the signals received by these arrays from a BLE device. It applies machine learning and a Bayesian probability filter to this data to generate a "probability surface." This surface is a statistical map that indicates the most likely location of the device, providing a more accurate and scalable solution than traditional methods.

A. trilateration: This is a simpler method that calculates location based on the RSSI from at least three fixed points. Mist's technique is more advanced, incorporating machine learning and beamforming.

B. triangulation: This method calculates location using the angles from known points, which is not the primary technique used by Mist's vBLE array and AI engine.

D. time of flight: This measures the signal's travel time to determine distance. It is a different technology, commonly associated with Ultra-Wideband (UWB), not Mist's core BLE location service.

1. Juniper Mist Whitepaper: Location, Location, Location: A Guide to Deploying Wi-Fi and Bluetooth LE Location Services.

Reference: Page 6, Section "Mist vBLE Technology".

Quote: "The Mist cloud uses a Bayesian probability filter to create a probability surface for each mobile device, which is used to estimate its location."

2. Juniper Mist Documentation: Location Services.

Reference: Section on "Virtual Bluetooth LE (vBLE)".

Content: The documentation explains that the vBLE array, combined with machine learning in the Mist cloud, provides scalable and accurate location services. It describes how the system moves beyond simple RSSI-based trilateration to a more advanced probabilistic model.

3. Juniper Networks Official Website: What is vBLE?

Reference: Technology description page.

Content: This resource details how the 16-element antenna array and cloud-based machine learning work together to calculate location with high accuracy, implicitly describing the process that results in a probability surface rather than simple geometric calculations like trilateration or triangulation.