18732438. GEOLOCATION OF WIRELESS NETWORK USERS simplified abstract (AT&T Intellectual Property I, L.P.)
Contents
GEOLOCATION OF WIRELESS NETWORK USERS
Organization Name
AT&T Intellectual Property I, L.P.
Inventor(s)
Abhijeet Bhorkar of Fremont CA (US)
Baofeng Jiang of Pleasanton CA (US)
GEOLOCATION OF WIRELESS NETWORK USERS - A simplified explanation of the abstract
This abstract first appeared for US patent application 18732438 titled 'GEOLOCATION OF WIRELESS NETWORK USERS
The method described in the abstract involves selecting a machine learning model for geolocation within a specific cell of a wireless network, acquiring event data from multiple wireless devices in that cell, grouping the data into records, and using the model to predict the location of a wireless device based on the input data.
- Selecting a machine learning model for geolocation within a specific cell of a wireless network
- Acquiring event data from multiple wireless devices in the selected cell
- Grouping the event data into records based on common device, cell, and timestamp
- Using the machine learning model to predict the location of a wireless device
- Outputting the predicted location based on the input data from the records
Potential Applications: - Enhanced location tracking for wireless devices - Improved network optimization and management - Enhanced security measures for wireless networks
Problems Solved: - Efficient geolocation within wireless networks - Enhanced data analysis for network management - Improved accuracy in predicting device locations
Benefits: - Enhanced network performance - Improved security measures - Streamlined data analysis processes
Commercial Applications: - Telecommunications industry for network optimization - IoT devices for accurate location tracking - Security companies for enhanced surveillance measures
Questions about Geolocation Technology: 1. How does the machine learning model improve location accuracy in wireless networks? 2. What are the potential challenges in implementing this technology on a large scale?
Frequently Updated Research: - Ongoing studies on improving machine learning models for geolocation accuracy - Research on enhancing data processing techniques for wireless network optimization.
Original Abstract Submitted
A method includes selecting a first machine learning model from a plurality of machine learning models that are trained for use in performing geolocation, wherein the first machine learning model is selected to perform geolocation within a first cell of a plurality of cells of a wireless network, acquiring event data from a plurality of wireless devices within the first cell, grouping the event data into a plurality of records, wherein each record of the plurality of records contains event data that indicates a common wireless device of the plurality of wireless devices, a common cell of the plurality of cells, and a common timestamp, and generating a predicted location of a first wireless device of the plurality of wireless devices, using the first machine learning model, wherein the first machine learning model outputs the predicted location in response to an input of a record of the plurality of records.
