公开(公告)号：WO2022200601A1

公开(公告)日：2022-09-29

申请号：PCT/EP2022/057986

申请日：2022-03-25

Applicant: BASF SE

Inventor： RAMIREZ HERNANDEZ, Tzutzuy ,  BEADLE, Andrew David ,  HAERING, Tim ,  MORAN PUENTE, Diana Westfalia ,  PERI, Venkata Ramana ,  PRIESE, Benjamin

IPC: G06Q50/02 ,  G06Q10/06

Abstract: A computer-implemented method for determining a treatment schedule for treating an agricultural field, comprising the following steps: (step A1) receiving by the computing unit – from a database and/or from user input and/or from real-time measurements –- crop data relating to the crop(s) planted or to be planted in the field(s) or sub-field zone(s) and indicative of at least one crop parameter, and- field data relating to the field(s) or sub-field zone(s) and indicative of at least one field environment parameter and/or field farming parameter, and- soil data relating to the field(s) or sub-field zone(s) and indicative of at least one soil-carbon parameters and/or soil-physical parameter,- optionally regulatory data relating to the field(s) or the sub-field zone(s),(step A2) at least based on the crop data, and the field data, and the soil data, generating a soil-related sustainability score for a field or a sub-field zone using a scoring model, wherein the scoring model is dependent on the following parameter groups:(PG1) crop parameter(s),(PG2) soil-carbon parameter(s), and/or soil-physical parameter(s), and(PG3) field environment parameter(s), and/or field farming parameter(s), (step A3) determining at least one treatment schedule based on the generated soil-related sustainability score.

公开(公告)号：WO2022243500A1

公开(公告)日：2022-11-24

申请号：PCT/EP2022/063690

申请日：2022-05-20

Applicant: BASF SE

Inventor： LOEFFEL, Christoph ,  HAUSEN, Tobias ,  PRIESE, Benjamin ,  PERI, Venkata Ramana ,  CHRISTEN, Thomas ,  MERK, Michael

IPC: G06Q10/04

Abstract: A computer-implemented method (100) for estimating a consumption of an agricultural product for an area of a geographical region cultivated with a specific crop, the method comprising the steps: providing (110) crop growth index data for the geographical region; determining (120) an area of the geographical region cultivated with a specific crop at least based on a comparison of the provided crop growth index data with plant-specific reference data; providing (130) a product consumption model for the agricultural product configured to estimate a consumption of the agricultural product at least based on the area of the geographical region cultivated with the specific crop; providing (140) an estimation of the consumption of the agricultural product for the determined area of the geographical region cultivated with the specific crop for the geographical region at least based on the determined area cultivated with the specific crop using the product consumption model.

公开(公告)号：WO2021156157A1

公开(公告)日：2021-08-12

申请号：PCT/EP2021/052193

申请日：2021-01-29

Applicant: BASF SE

Inventor： FANIDAKIS, Nikolaos ,  NEUMANN, Claus-Juergen ,  PRIESE, Benjamin ,  STROHMAIER, Frank ,  VOLKERT, Norman ,  CHRIST, Thomas ,  KNEITZ, Torsten Norbert ,  KUBISCH, Alexander

IPC: G05B23/02

Abstract: The present teachings relate to a method comprising a plurality of sensors, and one or more functionally connected processing units, the method comprising: providing, at any of the one or more processing units, time-series residual data of a sensor object; the sensor object being a group of at least some of the sensors from the plurality of sensors, and wherein the residual data comprises, for each of the sensors of the sensor object, a residue signal which is a difference between the sensor's measured output and the sensor's expected output, monitoring, via any of the one or more processing units, a level signal; wherein the level signal is indicative of a collective time-based variation of the time-series residual data, monitoring, via any of the one or more processing units, an association signal; wherein the association signal is indicative of the variation and/or association structure of the time-series residual data, generating, via any of the one or more processing units, an anomaly event signal when at a given time a value of the level signal and/or a value of the association signal changes from an expected value of the respective signal at or around that time. The present teachings also relate to a monitoring and/or control system for a plant comprising a plurality of sensors, wherein the system comprises one or more processing units configured to perform the method steps of any of the steps herein disclosed, and a computer software product.

公开(公告)号：EP4100808A1

公开(公告)日：2022-12-14

申请号：EP21702960.2

申请日：2021-01-29

Applicant: BASF SE

Inventor： FANIDAKIS, Nikolaos ,  NEUMANN, Claus-Juergen ,  PRIESE, Benjamin ,  STROHMAIER, Frank ,  VOLKERT, Norman ,  CHRIST, Thomas ,  KNEITZ, Torsten Norbert ,  KUBISCH, Alexander

IPC: G05B23/02

公开(公告)号：EP4497044A1

公开(公告)日：2025-01-29

申请号：EP23713886.2

申请日：2023-03-23

Applicant: BASF SE

Inventor： HACK, Katharina ,  PRIESE, Benjamin ,  HILDEBRANDT, Volker

IPC: G05B19/042 ,  G05B23/02

公开(公告)号：EP4341877A1

公开(公告)日：2024-03-27

申请号：EP22732004.1

申请日：2022-05-20

Applicant: BASF SE

Inventor： LOEFFEL, Christoph ,  HAUSEN, Tobias ,  PRIESE, Benjamin ,  PERI, Venkata Ramana ,  CHRISTEN, Thomas ,  MERK, Michael

IPC: G06Q10/04

公开(公告)号：EP4250250A1

公开(公告)日：2023-09-27

申请号：EP22164121.0

申请日：2022-03-24

Applicant: BASF SE

Inventor： PRIESE, Benjamin ,  KARAMI, Mojtaba ,  GEDMINAS, Laurynas ,  HAERING, Tim ,  DOERR, Manuel Josua ,  BOEHM, Julian ,  PFRANG, David ,  CHRIST, Thomas

IPC: G06V20/10

Abstract: The present invention generally relates to digital farming. In order to facilitate the provision of sensor data with a high spatial coverage, a computer-implemented method (100) is provided for training a data-driven model for measuring a concentration of a physicochemical parameter from a target field, the method comprising:
a) providing (110) historical satellite imagery data collected from at least one field over a period of time;
b) providing (120) historical sensor data collected from the at least one field, wherein the historical sensor data provides a measurement or an estimation of the concentration of the physicochemical parameter over the period of time; and
c) training (130) the data-driven model with a training dataset based on the provided historical satellite imagery data and the historical sensor data, wherein the trained data-driven model is usable as a soft-sensor for measuring a concentration of the physicochemical parameter from the target field based on satellite imagery data acquired from the target field.