# US 12,003,980 B2 · Portable generator dispatch recommendation engine > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 12,003,980 B2 - Document ID: US12003980B2 - Status: Granted - Kind: B2 - Application number: 17/871,074 - Filed: 2022-07-22 - Published: 2022-11-10 - Granted: 2024-06-04 - Earliest claimed: 2021-04-12 - Assignees: AT&T Intellectual Property I, L.P.; AT&T Mobility II LLC - Applicants: AT&T Intellectual Property I, L.P.; AT&T Mobility II LLC - Inventors: Matthew Osinski; Mark Brisbay; Zihui Ge; He Yan; Shuai Hao; Hector Perez; Gavin Anderson; Jason Tipton - Web page: https://patentgrep.com/patent/US12003980B2 ## CPC - H04W 24/02: Arrangements for optimising operational condition - H04W 24/04: Arrangements for maintaining operational condition - H04W 88/08: Access point devices - H04W: WIRELESS COMMUNICATION NETWORKS (broadcast communication H04H; communication systems using wireless links for non-selective communication, e.g. wireless extensions H04M1/72) ## Abstract Aspects of the subject disclosure may include, for example, detecting an interruption of a supply of operating power to a cell site of a cellular communication network, estimating an estimated time to restoration (ETR) of the supply of operating power to the cell site, wherein the estimating is based on information of an operator of the cellular communication network, determining, based in part on the ETR, to dispatch a portable generator to the cell site to provide a new supply of operating power to the cell site, and initiating a communication to dispatch the portable generator. Other embodiments are disclosed. ## Claims ### Claim 1 A device, comprising: a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations, the operations comprising: determining an interruption of a supply of power to a cell site of a cellular communication network; estimating an estimated time to restoration (ETR) of the supply of power to the cell site, wherein the estimating is based on a machine-learning model trained according to training data comprising information about the cell site; and determining, based in part on the ETR a response to the interruption of the supply of power to the cell site, wherein the response is determined based in part on the ETR. ### Claim 2 (depends on 1) The device of claim 1, wherein the operations further comprise: determining, by an operator of the cellular communication network, a number of cellular devices attaching to a cellular communication network; and detecting size, scope, and severity of the interruption in supply of power based on the number of cellular devices attaching to the cellular communication network exceeding a threshold. ### Claim 3 (depends on 2) The device of claim 2, wherein the operations further comprise: identifying a location of the cell site based on location of the cellular devices attaching to the cellular communication network. ### Claim 4 (depends on 2) The device of claim 2, wherein the operations further comprise: determining respective attachment times for the cellular devices attaching to the cellular communication network; determining respective locations of the cellular devices attaching to the cellular communication network; and detecting characteristics of the interruption in supply of power to the cell site based on the respective attachment times and the respective locations of the cellular devices. ### Claim 5 (depends on 1) The device of claim 1, wherein the operations further comprise: receiving technology information about technical features of the cell site, the technology information including at least information about a type of radio communication technology used by the cell site; and estimating the ETR based on the technology information. ### Claim 6 (depends on 5) The device of claim 5, wherein the operations further comprise: receiving location information about a physical location of the cell site; and estimating the ETR based on the location information. ### Claim 7 (depends on 6) The device of claim 6, wherein the operations further comprise: receiving utility company information about an electric power utility which provides the supply of power to the cell site; and estimating the ETR based on the utility company information. ### Claim 8 (depends on 1) The device of claim 1, wherein the operations further comprise: receiving, from an electric power utility which provides the supply of power to the cell site, a power provider estimated time to restoration; and identifying an alternate power source for the cell site based in part on the power provider estimated time to restoration. ### Claim 9 (depends on 1) The device of claim 1, wherein the operations further comprise: receiving an alarm from the cell site; and detecting the interruption in supply of power to the cell site based on the alarm. ### Claim 10 (depends on 1) The device of claim 1, wherein the operations further comprise: receiving an estimate of an impact to communication services based on the interruption in supply of power to the cell site; and identifying an alternate power source for the cell site based in part on a quantified estimate of customer impact. ### Claim 11 (depends on 1) The device of claim 1, wherein the response comprises initiating a communication to dispatch an alternate power source for the cell site. ### Claim 12 A non-transitory, machine-readable medium, comprising executable instructions that, when executed by a processing system including a processor, facilitate performance of operations, the operations comprising: identifying an interruption of a supply of power to a cell site of a cellular communication network; estimating an estimated time to restoration (ETR) of the supply of power to the cell site, wherein the estimating is based on a machine-learning model trained according to training data associated with communication technology of the cell site; and identifying, based on the ETR, an alternate power source for the cell site to provide a new supply of power to the cell site. ### Claim 13 (depends on 12) The non-transitory, machine-readable medium of claim 12, wherein the estimating the ETR comprises: providing the ETR to a decision engine, wherein the decision engine is configured to determine to dispatch the alternate power source. ### Claim 14 (depends on 13) The non-transitory, machine-readable medium of claim 13, wherein the operations further comprise: training a neural network as a machine learning model, wherein the training comprises providing to the neural network, technology information, utility company information or location information. ### Claim 15 (depends on 13) The non-transitory, machine-readable medium of claim 13, wherein the operations further comprise: determining, by the decision engine, to defer dispatching the alternate power source to the cell site for predetermined time. ### Claim 16 (depends on 13) The non-transitory, machine-readable medium of claim 13, wherein the operations further comprise: generating a trouble ticket, wherein the generating is in response to the identifying of the interruption of the supply of power to the cell site; and updating the trouble ticket based on a determination by the decision engine. ### Claim 17 (depends on 12) The non-transitory, machine-readable medium of claim 12, wherein the operations further comprise: determining a type of radio communication technology used by the cell site; determining a type of backhaul communication for backhaul data used by the cell site; and estimating the ETR based on the type of radio communication technology or the type of backhaul communication for backhaul data, or both. ### Claim 18 A method, comprising: identifying, by a processing system including a processor, an indication of an interruption of a supply of power to a cell site of a cellular communication network; receiving, by the processing system, an estimated time to restoration (ETR) of the supply of power to the cell site based on a machine learning model trained according to training data; and determining, by the processing system, a response to the interruption of the supply of power to the cell site, wherein the response is determined based in part on the ETR. ### Claim 19 (depends on 18) The method of claim 18, comprising: determining, by the processing system, to dispatch an alternate power source to the cell site to provide a new supply of power to the cell site. ### Claim 20 (depends on 18) The method of claim 18, comprising: identifying, by the processing system, a group of cellular devices attaching to the cellular communication network; determining, by the processing system, location information for the group of cellular devices; and based on the identifying and the location information, producing, by the processing system, the indication of the interruption of the supply of power to the cell site.