METHOD AND CONTROL SYSTEM FOR CONTROLLING AN AGRICULTURAL INSTALLATION FOR SMALL LIVESTOCK FARMING AND/OR MEDIUM LIVESTOCK FARMING

Abstract

A method for controlling an agricultural installation for small and medium livestock farming includes the steps of: acquiring at least one sensor signal of a sensor device of the agricultural installation configured for measuring a process or state variable in the agricultural installation; acquiring a plurality of further sensor signals from locally in the agricultural installation or from sensor devices distributed locally in another agricultural installation, wherein the distributed sensor devices are configured to measure process or state variables; storing the acquired sensor signals as cloud data in a cloud computing device; evaluating the sensor signal with an evaluation module, wherein the evaluation module is part of a control device of the agricultural installation and/or of a cloud computing device and wherein the evaluation takes at least a portion of the stored cloud data into consideration in order to verify the sensor signal in relation to the stored cloud data.

Claims

1-33. (canceled)

34. A method for controlling an agricultural installation for small or medium livestock farming, including chicken farming or pig farming, comprising the steps of: acquiring at least one first sensor signal of a first sensor device of the agricultural installation, wherein the first sensor device is configured for measuring a process variable or state variable in the agricultural installation; acquiring a plurality of further sensor signals from sensor devices distributed locally in the agricultural installation or from sensor devices distributed locally in another agricultural installation, wherein the distributed sensor devices are configured to measure process variables or state variables in the agricultural installation; storing the acquired sensor signals as cloud data in a cloud computing device; and evaluating the first sensor signal with an evaluation module, wherein the evaluation module is part of a control device of the agricultural installation or part of a cloud computing device, wherein the evaluation comprises taking at least a portion of the stored cloud data into consideration to verify the first sensor signal in relation to the stored cloud data.

35. The method as claimed in claim 34, wherein the method comprises the additional step of: generating one or more verified control signals to control at least one regulator of the agricultural installation, wherein: the one or more verified control signals is a control signal generated on the basis of the combined evaluation of the first sensor signal and the cloud data; the one or more control signals is part of a closed-loop control system of the agricultural installation; or the one or more control signals are prioritised and have priorities which can be configured differently.

36. The method as claimed in claim 34, wherein the method comprises the additional step of: generating one or more verified warning signals to indicate a warning and/or to indicate a perturbation of the agricultural installation, wherein the verified warning signal is a warning signal which is generated on the basis of the combined evaluation of the first sensor signal and the cloud data.

37. The method as claimed in claim 34, wherein the method comprises the additional steps of: generating one or more verified suggestions for optimised operating parameters or operational settings of the agricultural installation, wherein the verified suggestion is a suggestion which is generated based on the combined evaluation of the first sensor signal and the cloud data; and/or executing at least one action after detection of a discrepancy between the first sensor signal and the stored cloud data from the list of actions including: providing an extract of the first sensor signal and recorded cloud data; indicating a suggestion for modifying the operating parameters or for operational settings of the agricultural installation; or indicating a suggestion for a control of a regulator of the agricultural installation; wherein an actuation of said actions is executed in relation to a specific measurement of the detected discrepancy.

38. The method as claimed in claim 34, wherein before storage of the cloud data in the cloud computing device and/or the agricultural installation, at least one of the following steps is carried out: receiving the acquired sensor signals as raw data in a concentration module; or processing the raw data with the concentration module and storing the processed raw data as cloud data.

39. The method as claimed in claim 38, wherein processing of the raw data comprises anonymising the cloud data, compression, encoding and/or categorisation of the raw data.

40. The method as claimed in claim 34, wherein the measured process variable and/or state variable of the first sensor device and/or the measured process variables and/or state variables of the distributed sensor devices are variables for characterizing a barn climate in the agricultural installation, and the process variables and/or state variables are variables from the list including: a process variable and/or state variable for characterizing a harmful gas concentration (CO, CO.sub.2, H.sub.2S, NH.sub.3); a process variable and/or state variable for characterizing a brightness value for light, including during the diurnal cycle; a process variable and/or state variable for characterizing a composition of the light; a process variable and/or state variable for characterizing an amount of fresh air; a process variable and/or state variable for characterizing a movement of air; a process variable and/or state variable for characterizing a dust concentration; a process variable and/or state variable for characterizing a temperature; a process variable and/or state variable for characterizing a humidity; and a process variable and/or state variable for characterizing a level of noise; wherein the variables for characterizing the barn climate are measured with at least one barn climate sensor comprising any of a barn climate sensor as a gas sensor, a light sensor, a flow sensor, a dust sensor, a temperature sensor, and/or a humidity sensor.

41. The method as claimed claim 34, wherein the measured process variable and/or state variable of the first sensor device and/or the measured process variables and/or state variables of the distributed sensor devices are variables for characterizing a physiological and/or ethological mechanism of a behaviour of a farm animal in the agricultural installation, and the process variables and/or state variables are variables from the list including: a process variable and/or state variables for characterizing wallowing of the farm animals; a process variable and/or state variables for characterizing piling of the farm animals; a process variable and/or state variables for characterizing seeking shade in the farm animals; a process variable and/or state variables for characterizing shivering of the farm animals from cold; a process variable and/or state variables for characterizing panting of the farm animals; and a process variable and/or state variables for characterizing the food intake of the farm animals; wherein the variables for characterizing the physiological and/or ethological mechanism of a behaviour of the farm animal in the agricultural installation are measured with a camera system configured with an image recognition algorithm for detecting a physiological and/or ethological mechanism in the farm animal behaviour, and configured for recording and evaluating a profile of the movement of individual farm animals.

42. The method as claimed in claim 34, wherein the method comprises the additional steps of: using a camera system as the first sensor device, which is equipped with an image recognition algorithm for detecting a physiological and/or the ethological mechanism in the farm animal behaviour; using barn climate sensors as the distributed sensor devices for measuring variables for the characterization of a barn climate in the agricultural installation; and evaluating the first sensor signal presented as a camera signal from the first sensor device with the evaluation module, wherein the evaluation comprises taking at least a portion of the stored cloud data into consideration to verify the physiological and/or the ethological mechanism in the farm animal behaviour measured with the camera system in relation to the variables stored as cloud data for the characterization of the barn climate in the agricultural installation.

43. The method as claimed in claim 34, wherein the step of evaluating the first sensor signal with an evaluation module comprises the additional step of: using a machine learning algorithm to evaluate the first sensor signal and the stored cloud data to verify the first sensor signal in relation to the stored cloud data with the machine evaluation algorithm, wherein: the machine learning algorithm is a trained artificial neural network for verifying the first sensor signal and the stored cloud data to verify the first sensor signal in relation to the stored cloud data with the trained neural network; or a cloud-based machine learning algorithm is used which is configured in the cloud computing device.

44. The method as claimed in claim 34, wherein the method comprises the additional step of: providing a user interface for receiving decision signals and for consideration in the decision module after generating a verified warning signal and/or after generating a verified suggestion for optimised operating parameters, wherein: a verified control signal for controlling at least one regulator of the agricultural installation is generated based on the decision signal; and/or adjustment of a machine learning algorithm, a big data algorithm, and/or a cloud computing algorithm is carried out based on the decision signal, wherein the algorithm or the algorithms are configured to verify the first sensor signal.

45. The method as claimed in claim 34, wherein the step of evaluating the first sensor signal with an evaluation module comprises the additional step(s) of: assessing the first sensor signal in relation to the stored cloud data in respect of its control effectiveness, and determining an effectiveness as a measure of the control effectiveness of the first sensor signal; assessing the first sensor signal in relation to the stored cloud data in respect of the correct functionality of the sensor device, and determination of a functionality value as a measure of the functionality of the first sensor device; assessing the first sensor signal in relation to the stored cloud data in respect of a discrepancy between the sensor signal and the stored cloud data, and determining a value for the discrepancy as a measure of the discrepancy between the first sensor signal and the cloud data; assessing the first sensor signal in relation to the stored cloud data in respect of a plausibility of the sensor signal compared with the stored cloud data, and determining a plausibility value as a measure of the plausibility of the first sensor signal with respect to the cloud data; and/or indicating conspicuous sensor data after the evaluation to provide the conspicuous sensor data to a user for verification.

46. The method as claimed in claim 34, wherein the method comprises the additional step of: receiving an execution confirmation from the installation operator or an operations centre, wherein; after the expiry of a predetermined time period, a control signal for controlling at least one regulator of the agricultural installation is generated if no execution confirmation is received by the control device; and schedules are stored in the control device to generate a control signal for controlling the at least one regulator of the agricultural installation, wherein the schedules for execution confirmations differ as a function of time and/or situation.

47. The method as claimed in claim 34, wherein the method comprises the additional step of: generating a control signal to control at least one regulator of the agricultural installation if a modified sensor value is presented within a predetermined time period.

48. The method as claimed in claim 34, wherein the method comprises the additional step of: indicating the control actions which are initiated with additional information, wherein a control action is initiated by controlling by a control signal to control at least one regulator of the agricultural installation.

49. The method as claimed in claim 34, wherein the method comprises the additional step of: adjusting an effect of the cloud data for a subsequent evaluation based on further cloud data.

50. The method as claimed in claim 34, wherein the step for storage of the acquired sensor signals as cloud data in the cloud computing device comprises the additional step of: storing cloud data of other agricultural installations which, with reference to the agricultural installation to be controlled, are in a location: with a similar climate which is not less than 100 km away from the agricultural installation to be controlled; with a latitude which is no more than ?10 points of latitude from the location of the installation to be controlled; with a height above sea level which differs by less than 300 m from the installation to be controlled; and/or which originates from the same province or country as the agricultural installation to be controlled.

51. The method as claimed in claim 50, wherein the step of storage of the acquired sensor signals as cloud data in the cloud computing device is executed more frequently than every 120 minutes.

52. The method as claimed in claim 34, wherein a plurality of sensor devices are taken into consideration in the method, wherein the plurality of sensor devices comprises more than 100 sensor devices taken into consideration in the method; and/or a plurality of sensor devices from other agricultural installations are taken into consideration in the method wherein the plurality of sensor devices for other agricultural installations comprises more than 100 sensor devices from other agricultural installations taken into consideration in the method.

53. The method as claimed in claim 34, wherein the method comprises the additional step(s) of: determining a measure for a discrepancy and/or for a reliability of the first sensor signal in relation to the stored cloud data; generating one or more verified control signals, verified warning signals, and/or verified suggestions, wherein the verified control signal, the verified warning signal, and/or the verified suggestion is generated as a function of the measure of the discrepancy and/or of the reliability; and/or adjusting or modifying the first sensor signal as a function of the measure of the discrepancy and/or of the reliability.

54. The method as claimed in claim 34, wherein the method comprises the additional step(s) of: modifying or adjusting the first sensor signal in relation to the cloud data after the verification, so that the first sensor signal, after the modification or adjustment, differs less from the cloud data; and/or interpolating several first sensor signals and/or several further sensor signals with an interpolation function and modifying or adjusting the first sensor signal as a function of the interpolation function to provide an interpolated first sensor signal for controlling the agricultural installation.

55. The method as claimed in claim 34, wherein the control device is part of a closed-loop control system with optimization of different nominal parameters and the different nominal parameters have a priority which can be configured differently.

56. The method as claimed in claim 34, wherein the step of evaluating the first sensor signal with the evaluation module comprises the additional step of: evaluating the cloud data in an online mode of the control device, when a regular data connection with the cloud computing device is detected, and switching to a local mode of the control device when no regular data connection with the cloud computing device is detected.

57. The method as claimed in claim 34, wherein the method comprises the additional step of: processing data stored locally in the control device and/or stored cloud data by a machine learning algorithm, a big data algorithm, and/or a cloud computing algorithm to verify the first sensor signal.

58. The method as claimed in claim 34, wherein the method comprises the additional step of: generating one or more verified control signals to control at least one regulator of the agricultural installation, wherein the verified control signal is a control signal which is generated based on the combined evaluation of the first sensor signal and the cloud data, only when an approval signal is received via a user interface.

59. A control system for controlling an agricultural installation for small livestock farming and/or medium livestock farming, comprising: a first sensor device for acquiring at least one first sensor signal, wherein the first sensor device is part of the agricultural installation and is configured to measure a process variable and/or state variable of the agricultural installation; a plurality of sensors distributed locally in the agricultural installation for acquiring a plurality of further sensor signals and/or a plurality of sensors distributed locally in another agricultural installation for acquiring a plurality of further sensor signals, wherein the distributed sensor devices are configured for measuring process variables and/or state variables of the agricultural installation; a cloud computing device configured to store the acquired sensor signals as cloud data; and a control device configured to control the agricultural installation, wherein the control device has an evaluation module for evaluating the first sensor signal, and wherein the evaluation comprises taking at least a portion of the stored cloud data into consideration to verify the first sensor signal in relation to the stored cloud data with the evaluation module.

60. The control system as claimed in claim 59, wherein: the control device is configured to generate a verified control signal to control at least one regulator of the agricultural installation, wherein the verified control signal is a control signal which is generated based on the combined evaluation of the first sensor signal and the cloud data; the control device is configured for generating a verified warning signal to indicate a warning and/or a perturbation of the agricultural installation, wherein the verified warning signal is a warning signal, which is generated based on the combined evaluation of the first sensor signal and the cloud data; and/or the control device is configured to generate a verified suggestion for optimised operating parameters of the agricultural installation, wherein the verified suggestion is a suggestion for optimised operating parameters which is generated based on the combined evaluation of the first sensor signal and the cloud data.

61. The control system as claimed in claim 59, wherein the control system further comprises: at least the first sensor device; the distributed sensor devices; the cloud computing device; a display for indicating verified warning signals; a display for indicating verified suggestions for optimized operating parameters; a concentration module for receiving the acquired sensor signals as raw data and for processing the raw data as cloud data; and/or a user interface for receiving user inputs which are taken into consideration in the control device.

62. A computer program product comprising commands which, when the computer program product is executed by a computer, enables it to carry out the steps of the method as claimed in claim 34.

63. A computer-readable storage medium comprising commands which, when executed by a computer, enable it to carry out the steps of the method as claimed in claim 34.

64. A computer-readable data carrier on which the computer program product as claimed in claim 62 is stored.

65. A data carrier signal, which transfers the computer program product as claimed in claim 62.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0161] FIG. 1 diagrammatically shows a control system for controlling an agricultural installation for small livestock farming and/or medium livestock farming in an embodiment in accordance with the invention.

[0162] FIG. 2 diagrammatically shows a flow diagram for the method in accordance with the invention for controlling an agricultural installation for small livestock farming and/or medium livestock farming.

[0163] FIG. 3 diagrammatically shows a first exemplary embodiment of the proposed control method or control system.

[0164] FIG. 4 diagrammatically shows a second exemplary embodiment of the proposed control method or control system.

DETAILED DESCRIPTION OF THE EMBODIMENTS

[0165] FIG. 1 diagrammatically shows a control system 10 for controlling an agricultural installation for small livestock farming and/or medium livestock farming.

[0166] The control system 10 comprises a first sensor device 100 for acquiring at least one first sensor signal MS1, wherein the first sensor device 100 is part of the agricultural installation and is configured to measure a process variable and/or state variable of the agricultural installation.

[0167] The control system 10 additionally comprises a plurality of sensors 200 distributed locally in the agricultural installation for acquiring a plurality of further sensor signals MS2 to MSn and/or a plurality of sensors 200 distributed locally in another agricultural installation for acquiring a plurality of further sensor signals MS2 to MSn, wherein the distributed sensor devices 200 are configured to measure process variables and/or state variables of the agricultural installation.

[0168] The control system 10 additionally comprises a cloud computing device 300 for storage of the acquired sensor signals MS2 to MSn as cloud data, Cdata. The storage of the first sensor signal MS1 is optional.

[0169] In addition, the control system 10 comprises a control device 400 for controlling the agricultural installation, wherein the control device 400 has an evaluation module 410 for evaluating the first sensor signal, MS1, wherein the evaluation comprises taking into consideration at least a portion of the stored cloud data, Cdata, in order to verify the first sensor signal MS1 in relation to the stored cloud data, Cdata, with the evaluation module 410.

[0170] FIG. 1 also shows that the control device 400 is configured to produce one or more verified control signals, TStell, for controlling at least one regulator Al to An of the agricultural installation, wherein the verified control signal is a control signal.

[0171] FIG. 1 also shows that the control device 400 is configured to produce one or more verified warning signals, Twarn, to indicate a warning and/or to indicate a perturbation of the agricultural installation. The warnings and/or perturbations can be signalled with signalling means or display means W1 to Wn.

[0172] FIG. 1 also shows that the control device 400 is configured to produce one or more verified suggestions, Tvor, for optimised operating parameters or for operational settings of the agricultural installation. The suggestions can be indicated on or with display means V1 to Vn.

[0173] In addition, FIG. 1 illustrates receipt of the acquired sensor signals as raw data in a concentration module 310 and processing the raw data with the concentration module 310 and storage of the processed raw data in the cloud device 300 as cloud data.

[0174] In addition, FIG. 1 illustrates the provision of a user interface 420 for receiving decision signals, Tent, and for taking them into consideration in the decision module 410.

[0175] In addition, FIG. 1 demonstrates the function of the cloud computing device. This comprises a cloud module 330 which can also be considered to be a cloud application. This application is connected to a cloud database system 320 via an interface. The cloud application sends a database request, Rx, to the cloud database system 320. It responds with the provision of the requested cloud data, Tx.

[0176] FIG. 2 diagrammatically shows a flow diagram for a method for controlling an agricultural installation for small livestock farming and/or medium livestock farming.

[0177] The method comprises the step S1: acquiring at least one first sensor signal of a first sensor device of the agricultural installation, wherein the first sensor device is configured for measuring a process variable and/or state variable in the agricultural installation. The first sensor signal is, for example, the sensor signal MS1 from the sensor device 100, as can be seen in FIG. 1. The sensor device 100 is therefore, for example, a camera system and the first sensor signal MS1 is an image signal which describes the current optical state of the agricultural installation in the region of the image scanned by the camera, as a state variable.

[0178] In addition, the method comprises the step S2: acquiring a plurality of further sensor signals from locally in the agricultural installation and/or from sensor devices distributed locally in another agricultural installation, wherein the distributed sensor devices are configured to measure process variables and/or state variables in the agricultural installation. The plurality of the further sensor signals are, for example, the sensor signals MS2 to MDn of the sensor devices 200, as shown in FIG. 1. The sensor devices 200 are, for example, sensors for monitoring a barn climate in the agricultural installation, such as temperature sensors, noise sensors, light sensors, or the like. The distributed sensors 200 characterize the current state as regards temperature, the level of noise and light in the agricultural installation as state variables.

[0179] In addition, the method comprises the step S3: storing the acquired sensor signals as cloud data in a cloud computing device. The cloud computing device is, for example, configured as shown in FIG. 1 with a cloud module 330 or a cloud application and a cloud database system 320. It is envisaged that at least the acquired further sensor signals of the distributed sensors 200 are stored in the cloud, but in addition, the first sensor signal may also be stored in the cloud computing device.

[0180] In addition, the method comprises the step S4: evaluating the first sensor signal with an evaluation module, wherein the evaluation module is part of a control device of the agricultural installation and wherein the evaluation comprises taking at least a portion of the stored cloud data into consideration, in order to verify the first sensor signal in relation to the stored cloud data. The evaluation module is, for example, part of a control device, as shown in FIG. 1.

[0181] The method shown in FIG. 2 comprises further preferred steps which are not shown in FIG. 2. The preferred steps have been described above.

[0182] FIG. 3 shows a first exemplary embodiment, in which the quality of the first sensor signal is improved by external data from a specific cloud.

[0183] Because the values from many sensors are stored in a higher-level system, i.e., in the cloud, these are available both for a local evaluation by retaining data on a local system, and also directly in online mode.

[0184] FIG. 3 shows that a temperature sensor T1 with an accuracy of ?1 degrees Celsius measures an ambient temperature T1, for example 22? C. This means that the temperature T1 used in the control device 400 would normally be rounded to the nearest degree. In addition, in almost every space there is a temperature stratification which is height-dependent, which can be stored as temperature data or as a temperature profile as cloud data.

[0185] The accuracy of T1 is not sufficient in precision farming to control or regulate the described optimized production mechanisms, because the temperature delivered by the sensor differs by 2-3 degrees from the optimum temperature for rearing. It is now proposed to improve or to verify the temperature sensor T1 with additional data from the cloud device 300. To this end, in FIG. 3, further data from the sensors 200 as well as barn data are taken into consideration. By taking the additional data from the cloud into consideration, it can, for example, be determined that the temperature value T1=22? C. is not correct and a new verified value, T1,veri, is determined which corresponds to the actual value more accurately. This new value can then be used in the control device 400 in order to produce a sensor signal Tstell. In order to produce the new verified value, T1,veri, an algorithm is stored in the evaluation module. An example of an algorithm would be firstly to calculate a mean value from the three temperature sensors 100 to 200, and then to map the mean on a profile or on a look-up table and at the height of a chicken. Thus, a new value, T1,veri, can be generated and the exact temperature directly at chicken height can be determined. The control intervention which is generated is therefore more accurate and the overall efficiency of the installation increases.

[0186] FIG. 4 shows a second exemplary embodiment in which the quality of the first sensor signal is improved by external data from a specific cloud.

[0187] FIG. 4 shows that the prediction of an image interpretation considered in isolation might not be strong enough to be able to derive actions from it, which could have a negative effect on the wellbeing of the animal (for example, it could lead to death due to hyperthermia or hypothermia) or on weight gain. Accordingly, in order to confirm a camera interpretation, other sensor values from the barn (for example the mean of the temperature sensors in the barn) are taken into consideration, which together can result in a stronger predictive strength than the pure camera image itself. This is shown in FIG. 4 by a first sensor device 100 configured as a camera and the temperature sensors 200. In addition, an acoustic sensor 200 is provided to monitor the background noises.

[0188] The control device 400 is therefore configured with the evaluation module 410 to compare and verify the image signal, Tzittern, by means of cloud data. As an example, the camera image automatically detects that the monitored chickens are shivering, which is shown diagrammatically in FIG. 4. With the aid of the additional evaluation with the aid of the cloud data, which include temperature data and noise data, the image signal, Tzittern, can be verified and it can, for example, be verified that they are shivering from cold if the temperature is low and no loud noises have been detected.