# US 2024/0201697 A1 · Unmanned aerial vehicle deployment parameter modification > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2024/0201697 A1 - Document ID: US20240201697A1 - Status: Published application - Kind: A1 - Application number: 18/084,332 - Filed: 2022-12-19 - Published: 2024-06-20 - Earliest claimed: 2022-12-19 - Assignees: International Business Machines Corporation - Applicants: International Business Machines Corporation - Inventors: Martin G. Keen; Jana H. Jenkins; Xin Wang; Jennifer A. Mallette - Web page: https://patentgrep.com/patent/US20240201697A1 ## CPC - G05D 1/1064: {specially adapted for avoiding collisions with other aircraft} - B64C 39/024: {of the remote controlled vehicle type, i.e. RPV} - B64U 10/00: Type of UAV - G05D 1/104: {involving a plurality of aircrafts, e.g. formation flying (traffic control systems for aircraft G08G5/00)} - B64U 2101/20: for use as communications relays, e.g. high-altitude platforms - B64U 2101/30: for imaging, photography or videography - B64U 2201/10: autonomous, i.e. by navigating independently from ground or air stations, e.g. by using inertial navigation systems [INS] - G05D: SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES - B64C: AEROPLANES; HELICOPTERS - B64U: UNMANNED AERIAL VEHICLES [UAV]; EQUIPMENT THEREFOR ## Abstract A computer-implemented method, in accordance with one embodiment, includes obtaining observational data from an unmanned aerial vehicle (UAV) deployed in a working environment, the working environment including a plurality of entities carrying out tasks within the working environment. The data is analyzed to detect a disruption caused by the UAV to one or more of the entities within the working environment during the deployment. A parameter of a deployment is adjusted based on the analysis of the obtained data. ## Claims ### Claim 1 A computer-implemented method, comprising: obtaining observational data from an unmanned aerial vehicle (UAV) deployed in a working environment, the working environment including a plurality of entities carrying out tasks within the working environment; analyzing the data to detect a disruption caused by the UAV to one or more of the entities within the working environment during the deployment; and adjusting a parameter of a deployment based on the analysis of the obtained data. ### Claim 2 (depends on 1) The computer-implemented method of claim 1, wherein the obtained data includes audio/video (A/V) data collected by the UAV, wherein the analyzing includes using image and/or audio analysis techniques to determine the disruption caused by the UAV. ### Claim 3 (depends on 1) The computer-implemented method of claim 1, wherein the obtained data includes video data collected by the UAV, wherein the analyzing includes performing an image analysis techniques with a convolutional neural network (CNN). ### Claim 4 (depends on 1) The computer-implemented method of claim 1, wherein the obtained data includes audio data collected by the UAV, wherein the analyzing includes performing an audio analysis technique with a support vector machine (SVM). ### Claim 5 (depends on 1) The computer-implemented method of claim 1, wherein detecting a disruption caused by the UAV includes determining that an entity of the plurality of entities has changed positions due to mobility of and/or noise emitted from the UAV. ### Claim 6 (depends on 1) The computer-implemented method of claim 1, wherein detecting a disruption caused by the UAV includes determining that an entity of the plurality of entities has changed a gaze direction due to mobility of and/or noise emitted from the UAV. ### Claim 7 (depends on 1) The computer-implemented method of claim 1, wherein detecting a disruption caused by the UAV includes determining that an entity corresponding to a ground-based mode of transportation has reacted to presence of the UAV. ### Claim 8 (depends on 1) The computer-implemented method of claim 1, wherein the parameter of the deployment is selected from the group consisting of a present flight path of the UAV, a future flight path, a noise level of the UAV, a timing of a future deployment, and selection of a different UAV for a future deployment. ### Claim 9 (depends on 1) The computer-implemented method of claim 1, wherein the deployment is a present deployment of the UAV. ### Claim 10 (depends on 1) The computer-implemented method of claim 1, wherein the deployment is a future deployment of the UAV. ### Claim 11 (depends on 1) The computer-implemented method of claim 1, wherein the deployment is a future deployment of a swarm of UAVs. ### Claim 12 (depends on 1) The computer-implemented method of claim 1, comprising generating, based on the data, a heat map representing safe and unsafe geographical areas for the UAV to operate, wherein the heat map is used to alter and/or create a flight path that attempts to avoid the unsafe geographical areas. ### Claim 13 (depends on 1) The computer-implemented method of claim 1, comprising generating, based on the data, a heat map representing safe and unsafe geographical areas for the UAV to operate; using the heat map in conjunction with historical data to predict where unsafe geographical areas will be located in the future; and altering and/or creating a flight path for a future deployment that attempts to avoid the predicted unsafe geographical areas. ### Claim 14 (depends on 1) The computer-implemented method of claim 1, comprising generating, based on the data, a heat map representing safe and unsafe geographical areas for UAV operation; and outputting the heat map to a human operator for use in selecting a flight path for a deployment. ### Claim 15 A computer program product, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a computer to cause the computer to: obtain, by the computer, observational data from an unmanned aerial vehicle (UAV) deployed in a working environment, the working environment including a plurality of entities carrying out tasks within the working environment; analyze, by the computer, the data to detect a disruption caused by the UAV to one or more of the entities within the working environment during the deployment; and adjusting, by the computer, a parameter of a deployment based on the analysis of the obtained data. ### Claim 16 (depends on 15) The computer program product of claim 15, wherein the obtained data includes audio/video (A/V) data collected by the UAV, wherein the analyzing includes using image and/or audio analysis techniques to determine the disruption caused by the UAV. ### Claim 17 (depends on 15) The computer program product of claim 15, wherein detecting a disruption caused by the UAV includes determining that an entity of the plurality of entities has changed positions due to mobility of and/or noise emitted from the UAV. ### Claim 18 (depends on 15) The computer program product of claim 15, wherein detecting a disruption caused by the UAV includes determining that an entity of the plurality of entities has changed a gaze direction due to mobility of and/or noise emitted from the UAV. ### Claim 19 (depends on 15) The computer program product of claim 15, wherein detecting a disruption caused by the UAV includes determining that an entity corresponding to a ground-based mode of transportation has reacted to presence of the UAV. ### Claim 20 A system, comprising: a processor; and logic integrated with the processor, executable by the processor, or integrated with and executable by the processor, the logic being configured to: obtain observational data from an unmanned aerial vehicle (UAV) deployed in a working environment, the working environment including a plurality of entities carrying out tasks within the working environment; analyze the data to detect a disruption caused by the UAV to one or more of the entities within the working environment during the deployment; and adjust a parameter of a deployment based on the analysis of the obtained data.