# US 11,908,025 B2 · Highly responsive farming systems with extraordinary in-season optimization > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 11,908,025 B2 - Document ID: US11908025B2 - Status: Granted - Kind: B2 - Application number: 17/118,384 - Filed: 2020-12-10 - Published: 2021-06-17 - Granted: 2024-02-20 - Earliest claimed: 2019-12-11 - Assignees: Climate LLC - Applicants: Climate LLC - Inventors: Nick Nissing - Web page: https://patentgrep.com/patent/US11908025B2 ## CPC - G06Q 50/02: Agriculture; Fishing; Forestry; Mining - A01B 79/005: {Precision agriculture} - A01B 79/02: combined with other agricultural processing, e.g. fertilising, planting - G06N 20/00: Machine learning - G06V 20/188: {Vegetation} - A01B 69/001: {Steering by means of optical assistance, e.g. television cameras (steering devices for road marking vehicles E01C23/163)} - B64D 1/18: by spraying, e.g. insecticides - 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] - G06N 3/006: based on simulated virtual individual or collective life forms, e.g. social simulations or particle swarm optimisation [PSO] - G06N 3/126: Evolutionary algorithms, e.g. genetic algorithms or genetic programming - G06N 5/01: Dynamic search techniques; Heuristics; Dynamic trees; Branch-and-bound - G06V 20/13: Satellite images - G06V 20/194: {using hyperspectral data, i.e. more or other wavelengths than RGB} - G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR - A01B: SOIL WORKING IN AGRICULTURE OR FORESTRY; PARTS, DETAILS, OR ACCESSORIES OF AGRICULTURAL MACHINES OR IMPLEMENTS, IN GENERAL (making or covering furrows or holes for sowing, planting or manuring A01C5/00; mowers convertible to soil working apparatus or capable of soil working A01D42/04; mowers combined with soil working implements A01D43/12; soil working for engineering purposes E01, E02, E21) - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS - G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING - B64D: EQUIPMENT FOR FITTING IN OR TO AIRCRAFT; FLIGHT SUITS; PARACHUTES; ARRANGEMENT OR MOUNTING OF POWER PLANTS OR PROPULSION TRANSMISSIONS IN AIRCRAFT - B64U: UNMANNED AERIAL VEHICLES [UAV]; EQUIPMENT THEREFOR ## Abstract A method for controlling application of agrichemical products, comprises acquiring remotely sensed digital image data; developing a prescription to apply at least one agrichemical product in a variable manner based on at least the digital image data, wherein the prescription describes a plurality of passes of a particular autonomous vehicle over a field to apply the at least one agrichemical product; applying the at least one agrichemical product to a crop in the variable manner by the particular autonomous vehicle according to the prescription. ## Claims ### Claim 1 A method for controlling application of agrichemical products, comprising: acquiring remotely sensed digital image data, comprising: receiving a first set of data from a hotspot remote imagery subsystem; generating a set of diagnostic instructions based on the first set of data; and using the set of diagnostic instructions, remotely controlling a diagnostic scouting subsystem on a scouting mission to obtain a second set of data; developing a prescription to apply at least one agrichemical product in a variable manner based on at least the digital image data, wherein the prescription describes a plurality of passes of a particular autonomous vehicle over a field to apply the at least one agrichemical product; applying the at least one agrichemical product to a crop in the variable manner by the particular autonomous vehicle according to the prescription. ### Claim 2 (depends on 1) The method of claim 1, wherein the particular autonomous vehicle is an unmanned aerial vehicle. ### Claim 3 (depends on 1) The method of claim 1, wherein the prescription describes a mode of action that is different for at least one of the plurality of passes of the particular autonomous vehicle over the field to apply the at least one agrichemical product. ### Claim 4 (depends on 1) The method of claim 1, wherein the prescription describes a category of one of the at least one agrichemical product that is different for at least one of the plurality of passes of the particular autonomous vehicle over the field to apply the at least one agrichemical product. ### Claim 5 (depends on 1) The method of claim 1, wherein the prescription describes reapplication of the agrichemical product in a subsequent pass of the particular autonomous vehicle over the field, the subsequent pass occurring after a first pass of the plurality of passes of the particular autonomous vehicle over the field. ### Claim 6 (depends on 1) The method of claim 1, wherein the prescription is developed based on historical data from at least one prior growing season. ### Claim 7 (depends on 1) The method of claim 1, wherein the prescription is developed based on forecast weather events. ### Claim 8 (depends on 1) The method of claim 1, wherein the prescription comprises a pest control prescription, wherein the prescription is developed prior to and the agrichemical product is applied prior to a detection of pest or a detection of symptoms of pest within the field. ### Claim 9 (depends on 1) The method of claim 1, wherein the prescription comprises a pre-emergent prescription, wherein the prescription is developed prior to and the agrichemical product is applied prior to a detection of weed within the field. ### Claim 10 (depends on 1) The method of claim 1, wherein the agrichemical product includes an herbicide, an insecticide, a fungicide, a microbial, a micronutrient, a nitrogen-based fertilizer, a plant growth regulator, a defoliant, a soil amendment, or a combination thereof. ### Claim 11 (depends on 1) The method of claim 1, wherein the first set of data includes first multi-spectral images at a first resolution, and the second set of data includes second multi-spectral images at a second resolution that is higher than the first resolution. ### Claim 12 (depends on 11) The method of claim 11, wherein at least one set of multi-spectral images comprises hyperspectral images. ### Claim 13 (depends on 11) The method of claim 11, wherein the second set of data is obtained at a lower altitude than the first set of data. ### Claim 14 A method for controlling application of agrichemical products, comprising: acquiring remotely sensed digital image data; obtaining historical data from at least one prior growing season; developing a prescription to apply at least one agrichemical product in a variable manner based on the digital image data and the historical data, wherein the prescription describes a plurality of passes of a particular autonomous vehicle over a field to apply the at least one agrichemical product; applying the at least one agrichemical product to a crop in the variable manner by the particular autonomous vehicle according to the prescription. ### Claim 15 (depends on 14) The method of claim 14, wherein the historical data comprises at least one of: past prescriptions and corresponding prescription results, from a previous growing season prior to a current growing season; weed species and density from the previous growing season; insect damage from the previous growing season; disease severity from the previous growing season; soil data from the previous growing season; and yield information from the previous growing season. ### Claim 16 (depends on 14) The method of claim 14, wherein said historical data comprises spatial maps derived from imagery data using artificial intelligence or machine learning algorithms. ### Claim 17 (depends on 14) The method of claim 14, wherein the prescription describes a mode of action that is different for at least one of the plurality of passes of the particular autonomous vehicle over the field to apply the at least one agrichemical product. ### Claim 18 (depends on 14) The method of claim 14, wherein the prescription describes a category of one of the at least one agrichemical product that is different for at least one of the plurality of passes of the particular autonomous vehicle over the field to apply the at least one agrichemical product. ### Claim 19 (depends on 14) The method of claim 14, wherein acquiring the remotely sensed digital image data comprises: receiving a first set of data from a hotspot imagery subsystem; generating a set of diagnostic instructions based on the first set of data; using the set of diagnostic instructions, remotely controlling a diagnostic scouting subsystem on a scouting mission to obtain a second set of data.