Abstract: Location of objects within an identified subspace defined within a predefined master space. The system includes an RF beacon associated with an object, the RF beacon transmitting signals to one or more of RF tags transmitting to an object location system a tag data package including an identification of the signals received by the RF tags from the RF beacon. The system includes a gateway receiving and extracting, from the transmitted tag data package, the identification of signals. The system further includes the location engine accessing an ML model trained by performing a survey of RF signals received from a plurality of RF signal sources during a prior RF master space survey operation and determining a subspace identifier corresponding to a predicted subspace location for the object by comparing the identification of signals included in the received tag data package to a model plurality of signals accessed from the model.

Abstract: Location of objects associated with radio frequency (RF) tags in a particular subspace or room within a predefined master space. A plurality of multi-channel radio beacons (e.g. Bluetooth Low Energy or BLE) transmit signals into the master space. A survey operation is conducted to detect RF signals, e.g. RSSI values, from the beacons within predefined subspaces within the master space. Data from the survey operation is used to construct one or more machine learning (ML) data models. Each object to be located is provided with a dual mode RF tag that receives beacon signals when placed into a subspace and activates (e.g. by motion or command) to transmit data containing RSSI of beacon signals to an object location system. The system runs the received beacon signals against the ML data models and returns a prediction candidate of a particular subspace corresponding to a likely location of the tag and object.