Mist AI uses reinforcement learning in its Radio Resource Management (RRM) service. This approach allows the system to dynamically optimize the performance of the wireless network by adjusting various radio parameters. The RRM service continuously learns and adapts based on network conditions, user behavior, and environmental factors to ensure optimal performance and reliability.

Line of Sight: For optimal accuracy and stability of location-based services, each access point (AP) should have an unobstructed line of sight to at least two other APs. This ensures robust triangulation and accurate location tracking.
Ceiling Mounting: Mounting APs on the ceiling with the LED facing the floor is recommended.
This position provides the best coverage and performance for both Wi-Fi and BLE signals, essential for reliable location services.

For capacity, coverage, and throughput Service Level Expectations (SLEs) in Mist AI, throughput is measured in Mbps. This unit measures the rate at which data is successfully delivered over the wireless network, providing a clear indication of network performance and user experience. Mist AI tracks these metrics to ensure the network meets the required performance standards.