Determining location using BLE signals
AssigneeHID Global Corporation
InventorsSrinjay Paul, Robert Kjell Rowe, Mark Robinton, Matthew Johnson
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Abstract
Methods and systems are provided for performing operations including: receiving a plurality of Bluetooth Low Energy (BLE) signals from a BLE beacon associated with an object over a period of time; generating a series of spatial patterns based on Received Signal Strength Indicators (RSSI) associated with the BLE signals; processing the series of spatial patterns by a first machine learning model to select a portion of the series of spatial patterns for use in determining a location of the object; and determining the location of the object based on the selected portion of the series of spatial patterns associated with the BLE signals.
Claims19
A method comprising:
- receiving a plurality of Bluetooth Low Energy (BLE) signals from a BLE beacon associated with an object over a period of time;
- generating a series of spatial patterns based on Received Signal Strength Indicators (RSSI) associated with the plurality of BLE signals;
- processing the series of spatial patterns by a first machine learning model comprising a Transformer Encoder Stack Neural Network model to select a portion of the series of spatial patterns for use in determining a location of the object, the Transformer Encoder Stack Neural Network model statistically analyzing the series of spatial patterns to discern which samples correspond to movement along a path and represent a location along a trajectory and which samples correspond to noise or duplicate data samples;
- and
- determining the location of the object based on the selected portion of the series of spatial patterns associated with the plurality of BLE signals.
A system comprising:
- one or more processors configured to perform operations comprising:
- receiving a plurality of Bluetooth Low Energy (BLE) signals from a BLE beacon associated with an object over a period of time;
- generating a series of spatial patterns based on Received Signal Strength Indicators (RSSI) associated with the plurality of BLE signals;
- processing the series of spatial patterns by a first machine learning model comprising a Transformer Encoder Stack Neural Network model to select a portion of the series of spatial patterns for use in determining a location of the object, the Transformer Encoder Stack Neural Network model statistically analyzing the series of spatial patterns to discern which samples correspond to movement along a path and represent a location along a trajectory and which samples correspond to noise or duplicate data samples;
- and
- determining the location of the object based on the selected portion of the series of spatial patterns associated with the plurality of BLE signals.
A non-transitory computer-readable medium comprising non-transitory computer-readable instructions that, when executed by one or more processors, configure the one or more processors to perform operations comprising:
- receiving a plurality of Bluetooth Low Energy (BLE) signals from a BLE beacon associated with an object over a period of time;
- generating a series of spatial patterns based on Received Signal Strength Indicators (RSSI) associated with the plurality of BLE signals;
- processing the series of spatial patterns by a first machine learning model comprising a Transformer Encoder Stack Neural Network model to select a portion of the series of spatial patterns for use in determining a location of the object, the Transformer Encoder Stack Neural Network model statistically analyzing the series of spatial patterns to discern which samples correspond to movement along a path and represent a location along a trajectory and which samples correspond to noise or duplicate data samples;
- and
- determining the location of the object based on the selected portion of the series of spatial patterns associated with the plurality of BLE signals.
Dependencies are inferred from the claim text.