# US 2025/0097664 A1 · Systems and methods for machine learning based location and directions for venue and campus networks > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2025/0097664 A1 - Document ID: US20250097664A1 - Status: Published application - Kind: A1 - Application number: 18/727,611 - Filed: 2023-05-15 - Published: 2025-03-20 - Earliest claimed: 2022-06-02 - Assignees: CommScope Technologies LLC - Applicants: CommScope Technologies LLC - Inventors: Harsha Hegde; Milind Kulkarni; Raymond Zachary Lovell - Web page: https://patentgrep.com/patent/US20250097664A1 ## CPC - H04W 4/021: Services related to particular areas, e.g. point of interest [POI] services, venue services or geofences - H04W 4/90: Services for handling of emergency or hazardous situations, e.g. earthquake and tsunami warning systems [ETWS] - G06N 20/00: Machine learning - H04W 4/024: Guidance services - H04W: WIRELESS COMMUNICATION NETWORKS (broadcast communication H04H; communication systems using wireless links for non-selective communication, e.g. wireless extensions H04M1/72) - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS ## Abstract Systems and methods for providing machine learning based location and directions for venue and campus network are provided. In one example, a system includes a BBU entity and RU(s) communicatively coupled to the BBU entity. The system further includes antenna(s) communicatively coupled to the RU(s), and each respective RU is communicatively coupled to a respective subset of the antenna(s). The BBU entity, the RU(s), and the antenna(s) are configured to implement a base station for wirelessly communicating with UEs in a cell. The system further includes a machine learning computing system configured to receive time and location data and determine a predicted density for location areas in the cell based on the time and location data. The system is configured to determine a target location based on the predicted density for the location areas in the cell and send the target location to a first UE in the cell ## Claims ### Claim 1 A system, comprising: at least one baseband unit (BBU) entity; one or more radio units communicatively coupled to the at least one BBU entity; one or more antennas communicatively coupled to the one or more radio units, wherein each respective radio unit of the one or more radio units is communicatively coupled to a respective subset of the one or more antennas; wherein the at least one BBU entity, the one or more radio units, and the one or more antennas are configured to implement a base station for wirelessly communicating with user equipment in a cell; and a machine learning computing system configured to receive time and location data and determine a predicted density for a plurality of location areas in the cell based on the time and location data; wherein the system is configured to: determine a target location based on the predicted density for the plurality of location areas in the cell; and send the target location to a first user equipment in the cell. ### Claim 2 (depends on 1) The system of claim 1, wherein the time and location data includes: a time of day; a day of week; and an identifier for at least one location area of the plurality of location areas in the cell. ### Claim 3 (depends on 1) The system of claim 1, wherein the system is further configured to determine a location of the first user equipment. ### Claim 4 (depends on 3) The system of claim 3, wherein the system is further configured to send, to the first user equipment, directions from the location of the first user equipment to the target location. ### Claim 5 (depends on 3) The system of claim 3, wherein the system is configured to determine the target location based on the location of the first user equipment. ### Claim 6 (depends on 3) The system of claim 3, wherein the system is further configured to send the location of the first user equipment to a first responder. ### Claim 7 (depends on 1) The system of claim 1, wherein the system is further configured to determine the target location by selecting the target location from a plurality of predetermined target locations in the cell. ### Claim 8 (depends on 1) The system of claim 1, wherein the system is further configured to determine a type of active emergency or alert in the cell, wherein the system is configured to determine the target location based on the type of active emergency or alert in the cell. ### Claim 9 (depends on 1) The system of claim 1, wherein the machine learning computing system is configured to utilize the time and location data as inputs to a plurality of machine learning models, wherein each machine learning model of the plurality of machine learning models is directed to a respective sub-area of the cell. ### Claim 10 (depends on 1) The system of claim 1, wherein the machine learning computing system is configured to utilize the time and location data as inputs to a plurality of machine learning models, wherein each machine learning model of the plurality of machine learning models is directed to a respective building or venue. ### Claim 11 (depends on 1) The system of claim 1, wherein the one or more radio units includes a plurality of radio units, wherein the one or more antennas includes a plurality of antennas, wherein the at least one BBU entity includes a central unit communicatively coupled to a distributed unit, wherein the distributed unit is communicatively coupled to the one or more radio units, wherein the machine learning computing system is implemented in a radio access network intelligent controller. ### Claim 12 (depends on 1) The system of claim 1, wherein the system is configured to provide directions to the target location via lights and/or signs of a venue, wherein the system is configured to send control signals to the lights and/or signs of the venue to enable/disable the lights and/or signs. ### Claim 13 A method, comprising: receiving time data and location data; determining a predicted density for a plurality of location areas in a cell based on the time data and the location data, wherein at least one baseband unit (BBU) entity, one or more radio units, and one or more antennas are configured to implement a base station for wirelessly communicating with user equipment in the cell, wherein the one or more radio units communicatively coupled to the at least one BBU entity, wherein the one or more antennas are communicatively coupled to the one or more radio units, wherein each respective radio unit of the one or more radio units is communicatively coupled to a respective subset of the one or more antennas; determining a target location based on the predicted density for the plurality of location areas in the cell; and sending the target location to a first user equipment in the cell. ### Claim 14 (depends on 13) The method of claim 13, wherein the time data and the location data includes: a time of day; a day of week; and an identifier for at least one location area of the plurality of location areas in the cell. ### Claim 15 (depends on 13) The method of claim 13, further comprising determining a location of the first user equipment. ### Claim 16 (depends on 15) The method of claim 15, further comprising sending, to the first user equipment, directions from the location of the first user equipment to the target location. ### Claim 17 (depends on 15) The method of claim 15, wherein the method comprises determining the target location based on the predicted density for the plurality of location areas in the cell and the location of the first user equipment. ### Claim 18 (depends on 13) The method of claim 13, wherein determining the target location based on the predicted density for the plurality of location areas in the cell includes selecting the target location from a plurality of predetermined target locations in the cell. ### Claim 19 (depends on 13) The method of claim 13, further comprising determining a type of active emergency or alert in the cell, wherein the method comprises determining the target location based on the predicted density for the plurality of location areas in the cell and the type of active emergency or alert in the cell. ### Claim 20 (depends on 13) The method of claim 13, further comprising providing directions to the target location via lights and/or signs of a venue by sending control signals to the lights and/or signs of the venue to enable/disable the lights and/or signs.