Intelligent grassland grazing management system and method based on Internet of Things

Abstract

The invention discloses a grassland intelligent grazing management system and method based on the Internet of Things, and the system comprises a data collection module which collects the related data of a pasture through a sensor; the data transmission module is used for transmitting the data acquired by the data acquisition module to the data processing module; the data processing module comprises a server and a data processing module, the server receives the data from the data transmission module, and the data processing module preprocesses the data to obtain a management strategy and early warning information; the decision and control module is used for receiving the management strategy and the early warning information generated by the data processing module and making decisions according to preset rules and algorithms; and the user interaction module provides a visual operation interface for a user, and the user logs in the system through terminal equipment and manages parameter setting and rule adjustment of the system. According to the method, the utilization efficiency of grassland resources can be improved, the livestock breeding risk is reduced, the labor cost is reduced, and grassland grazing management is promoted to develop towards the intelligent and scientific direction.

Description

Technical Field

[0001] The present invention relates to the field of intelligent farming, and in particular to an Internet of Things-based grassland intelligent grazing management system and method. Background Art

[0002] Against the backdrop of the global livestock industry's continued development and the growing demand for livestock products, the scientific and efficient management of grassland grazing, a crucial component of the sector, has become increasingly crucial. Furthermore, the rise of IoT technology has provided strong support for intelligent upgrades across various industries. The livestock industry also hopes to leverage the IoT to transition from traditional grazing to intelligent grazing management, thereby improving grassland resource utilization and livestock breeding efficiency, meeting market demand for high-quality livestock products, and promoting the sustainable development of the sector.

[0003] However, existing grassland grazing management technologies present numerous problems. For one thing, monitoring methods for grassland ecosystems are relatively backward, mostly relying on regular manual inspections and simple equipment monitoring. These methods are unable to obtain real-time and comprehensive information on soil moisture, light intensity, forage growth, and other aspects of grassland, making it difficult to achieve precise management of grassland resources. Furthermore, in livestock management, traditional methods rely primarily on manual observation and empirical judgment, failing to accurately grasp key information such as livestock health and activity patterns. This results in delayed disease prevention and control and irrational grazing planning. Furthermore, the application of IoT technology in grassland grazing management lacks systematicity, and the data exchange and collaborative working capabilities between devices are insufficient, making it impossible to form effective management decisions. This severely restricts the development of intelligent grassland grazing management. Summary of the Invention

[0004] The purpose of this section is to summarize some aspects of the embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the abstract and title of this application to avoid obscuring the purpose of this section, the abstract and the title of the invention, and such simplifications or omissions should not be used to limit the scope of the present invention.

[0005] In light of the above-mentioned existing problems, the present invention proposes an IoT-based intelligent grassland grazing management system to address the problems of traditional grassland grazing livestock management, which relies on manual experience and lacks systematic application of IoT technology, making it difficult to achieve precise grassland resource management, timely disease prevention and control, and reasonable grazing planning.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] In a first aspect, the present invention provides a grassland intelligent grazing management system based on the Internet of Things, comprising:

[0008] The data acquisition module uses sensors to collect ranch-related data and sends the data to the data transmission module through a wireless communication network;

[0009] A data transmission module, which transmits the data collected by the data acquisition module to the data processing module;

[0010] The data processing module includes a server and a data processing module. The server receives data from the data transmission module, and the data processing module pre-processes the data to obtain management strategies and early warning information;

[0011] The decision-making and control module receives the management strategies and warning information generated by the data processing module and makes decisions based on preset rules and algorithms;

[0012] The user interaction module provides users with a visual operation interface. Users log in to the system through terminal devices and manage the system's parameter settings and rule adjustments.

[0013] As a preferred solution of the Internet of Things-based grassland intelligent grazing management system described in the present invention, the data acquisition module uses sensors to collect pasture-related data and sends the data to the data transmission module through a wireless communication network, including:

[0014] Sensors are used to collect soil moisture data, light intensity and duration, pasture temperature, air quality, livestock location and activity trajectory, and pasture forage-related data.

[0015] As a preferred solution of the Internet of Things-based grassland intelligent grazing management system described in the present invention, the data transmission module transmits the data collected by the data acquisition module to the data processing module, including:

[0016] After the data transmission module receives various types of data from the data acquisition module, it uses the AES algorithm to encrypt the data to prevent the data from being stolen or tampered with;

[0017] Use data error correction technology to verify the transmitted data. If the data is found to be erroneous or lost, retransmit it.

[0018] Dynamically select the appropriate communication protocol and transmission method based on network conditions and data volume.

[0019] As a preferred solution of the Internet of Things-based grassland intelligent grazing management system described in the present invention, the data processing module includes a server and a data processing module. The server receives data from the data transmission module, and the data processing module pre-processes the data to obtain management strategies and early warning information, including:

[0020] After the server receives the data transmitted by the data transmission module, it cleans the data through the data processing module to remove duplicate, erroneous and invalid data, stores the cleaned data in the database, and establishes historical data records;

[0021] Based on soil moisture data, light intensity and duration, pasture temperature, historical data, and weather forecast information, machine learning algorithms are used to analyze the changing trends of pasture ecological environments and predict forage growth.

[0022] Analyze livestock activity patterns, group distribution, and health status based on their location and activity trajectories, and use machine learning models to identify abnormal livestock behaviors and health issues.

[0023] Based on the analysis results, corresponding management strategies are generated, warning thresholds for various types of data are set, and warning information is generated when the data exceeds the threshold.

[0024] As a preferred solution of the Internet of Things-based grassland intelligent grazing management system described in the present invention, the decision-making and control module receives the management strategy and warning information generated by the data processing module and makes decisions based on preset rules and algorithms, including:

[0025] After receiving the management strategies and warning information from the data processing module, the decision-making and control module compares and analyzes them with the preset rules and algorithms;

[0026] If the soil moisture is lower than the preset irrigation threshold, the decision and control module automatically sends an open command to the irrigation equipment to perform irrigation operations; if the soil moisture reaches the appropriate range after irrigation for a period of time, a close command is sent;

[0027] When livestock show abnormal health conditions, the decision-making and control module will promptly send an alarm message to the ranch manager's terminal device;

[0028] Based on forage growth and livestock distribution, the decision-making and control module rationally plans grazing areas and times, and guides livestock to appropriate grazing areas by controlling the opening and closing of fence equipment.

[0029] Dynamically adjust grazing time according to the grass growth conditions in different areas.

[0030] As a preferred solution of the Internet of Things-based grassland intelligent grazing management system of the present invention, it also includes:

[0031] The equipment control module is connected to various equipment in the ranch, receives control instructions from the decision and control module, and controls the equipment;

[0032] The equipment control module controls the sprinkler switch, water flow rate and irrigation time of the irrigation equipment according to the instructions of the decision and control module; controls the opening and closing of the fence equipment to limit or guide the range of livestock activities.

[0033] As a preferred solution of the Internet of Things-based grassland intelligent grazing management system described in the present invention, the user interaction module provides a visual operation interface for users, and users log in to the system through terminal devices to manage the system's parameter settings and rule adjustments, including:

[0034] On the operation interface, users can view the ranch's environmental data, livestock location and health information, and system-generated management strategies and early warning information in real time;

[0035] Displaying ranch data in the form of a map allows users to quickly understand the actual situation of the ranch;

[0036] Users manually input commands through the interface to remotely control irrigation equipment, fencing equipment, etc., set the collection time intervals of various sensors, data warning thresholds, and grazing area division rules.

[0037] In a second aspect, the present invention provides a method for a grassland intelligent grazing management system based on the Internet of Things, comprising:

[0038] Use sensors to collect pasture-related data and send the data to the data transmission module through the wireless communication network;

[0039] Transmitting the data collected by the data acquisition module to the data processing module;

[0040] The server receives data from the data transmission module, and the data processing module pre-processes the data to obtain management strategies and early warning information;

[0041] Based on the management strategies and early warning information generated by the data processing module, decisions are made according to preset rules and algorithms;

[0042] Provides a visual operation interface, users log in to the system through terminal devices and manage system parameter settings and rule adjustments.

[0043] In a third aspect, the present invention provides a computing device, comprising:

[0044] memory and processor;

[0045] The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, the steps of the grassland intelligent grazing management system based on the Internet of Things are implemented.

[0046] In a fourth aspect, the present invention provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the Internet of Things-based grassland intelligent grazing management system.

[0047] Compared with existing technologies, the present invention offers significant advantages: its decision-making and control module, based on pre-set rules and algorithms, automatically controls irrigation equipment, promptly issues livestock health alerts, and rationally plans grazing areas and schedules, achieving automated and intelligent pasture management. The equipment control module precisely controls various pasture equipment, further enhancing management accuracy. This system improves grassland resource utilization efficiency, reduces livestock breeding risks, and reduces labor costs, driving the development of intelligent and scientific pasture management. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. Those skilled in the art can also derive other drawings based on these drawings without inventive effort. Among them:

[0049] Figure 1 This is a schematic diagram of an IoT-based intelligent grassland grazing management system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0050] To make the above-mentioned objects, features, and advantages of the present invention more clearly understood, the following detailed description of the specific embodiments of the present invention is given in conjunction with the accompanying drawings. It is obvious that the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in this field without creative work should fall within the scope of protection of the present invention.

[0051] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0052] Secondly, the term "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in various places throughout this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive of other embodiments.

[0053] The present invention is described in detail with reference to schematic diagrams. For ease of illustration, cross-sectional views of device structures may be partially enlarged and not to scale when describing embodiments of the present invention. Furthermore, the schematic diagrams are merely illustrative and should not limit the scope of the present invention. Furthermore, in actual production, the three-dimensional dimensions of length, width, and depth should be included.

[0054] Furthermore, in the description of the present invention, it should be noted that the terms "upper, lower, inner, and outer" and other references to orientations or positional relationships are based on the orientations or positional relationships shown in the accompanying drawings and are intended solely to facilitate and simplify the description of the present invention. They are not intended to indicate or imply that the systems or components referred to must have, be constructed, or operate in a specific orientation, and therefore should not be construed as limitations on the present invention. Furthermore, the terms "first, second, or third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0055] In this disclosure, unless otherwise specified or limited, the terms "mounted," "connected," and "connected" should be interpreted broadly. For example, they may refer to fixed, removable, or integral connections. They may also refer to mechanical, electrical, or direct connections, indirect connections through an intermediary, or internal communication between two components. Those skilled in the art will understand the specific meanings of these terms in this disclosure.

[0056] Example 1

[0057] Reference Figure 1 , which is an embodiment of the present invention, provides a grassland intelligent grazing management system based on the Internet of Things, including:

[0058] The data acquisition module uses sensors to collect ranch-related data and sends the data to the data transmission module through a wireless communication network;

[0059] Preferably, sensors are used to collect soil moisture data, light intensity and duration, pasture temperature, air quality, livestock location and activity trajectory, and pasture forage-related data.

[0060] Specifically, high-precision soil moisture sensors are evenly installed at certain intervals in different areas of the pasture, and the sensors collect data every 30 minutes.

[0061] Light sensors are installed in open and unobstructed areas of the pasture to continuously monitor light intensity and record data in minutes.

[0062] Temperature sensors are installed in areas with different terrain and orientations within the ranch, collecting temperature data every hour to fully understand the temporal and spatial distribution of temperature within the ranch. The levels of oxygen, carbon dioxide, and harmful gases are also monitored.

[0063] Each livestock is equipped with a smart collar with high-precision positioning function. The collar has a built-in positioning sensor that uses the Global Positioning System or Beidou satellite positioning system to record the livestock's location information every minute and monitor the livestock's activity status through the built-in motion sensor.

[0064] Use forage growth monitoring sensors installed on mobile devices to conduct a comprehensive scan of the pasture and obtain real-time information such as forage height, density, and color.

[0065] All collected data is initially organized and packaged before being sent to the data transmission module in a stable and efficient manner. To ensure data transmission reliability, data is verified and encrypted before being sent to prevent data loss or tampering.

[0066] A data transmission module, which transmits the data collected by the data acquisition module to the data processing module;

[0067] Preferably, after the data transmission module receives various types of data from the data acquisition module, it uses the AES algorithm to encrypt the data to prevent the data from being stolen or tampered with; it uses data error correction technology to verify the transmitted data, and retransmits the data if errors or loss are found; and it dynamically selects the appropriate communication protocol and transmission method based on the network conditions and data volume.

[0068] The data processing module includes a server and a data processing module. The server receives data from the data transmission module, and the data processing module pre-processes the data to obtain management strategies and early warning information;

[0069] Preferably, after receiving the data transmitted by the data transmission module, the server cleans the data through the data processing module to remove duplicate, erroneous and invalid data, stores the cleaned data in the database, and establishes a historical data record;

[0070] Preferably, based on soil moisture data, light intensity and duration, pasture temperature, combined with historical data and weather forecast information, a machine learning algorithm is used to analyze the changing trends of the pasture ecological environment and predict forage growth;

[0071] Preferably, the livestock's activity patterns, group distribution, and health status are analyzed based on their location and activity trajectories, and machine learning models are used to identify abnormal behaviors and health problems of the livestock;

[0072] Preferably, a corresponding management strategy is generated based on the analysis results, warning thresholds are set for various types of data, and warning information is generated when the data exceeds the threshold.

[0073] The decision-making and control module receives the management strategies and warning information generated by the data processing module and makes decisions based on preset rules and algorithms;

[0074] Preferably, after receiving the management strategy and warning information from the data processing module, the decision and control module compares and analyzes them with the preset rules and algorithms;

[0075] Preferably, if the soil moisture is lower than a preset irrigation threshold, the decision and control module automatically sends an on command to the irrigation device to perform irrigation operations; if the soil moisture reaches an appropriate range after a period of irrigation, a off command is sent;

[0076] Preferably, when the livestock show abnormal health conditions, the decision and control module promptly sends an alarm message to the terminal device of the ranch manager;

[0077] Preferably, the decision and control module rationally plans the grazing area and time according to the forage growth and livestock distribution, guides the livestock to the appropriate grazing area by controlling the opening and closing of the fence equipment; and dynamically adjusts the grazing time according to the forage growth in different areas.

[0078] The decision-making and control module also includes an equipment control module, which is connected to various types of equipment in the pasture, receives control instructions issued by the decision-making and control module, and controls the equipment; the equipment control module controls the sprinkler switch, water flow size and irrigation time of the irrigation equipment according to the instructions of the decision-making and control module; controls the opening and closing of the fence equipment to limit or guide the range of livestock activities.

[0079] The user interaction module provides users with a visual operation interface. Users log in to the system through terminal devices and manage the system's parameter settings and rule adjustments;

[0080] Preferably, on the operation interface, users can view the ranch's environmental data, livestock location and health information, system-generated management strategies and early warning information in real time; the ranch data is displayed in the form of a map, making it easy for users to quickly understand the actual situation of the ranch;

[0081] Preferably, the user manually inputs instructions through the interface to remotely control irrigation equipment, fencing equipment, etc., set the collection time intervals of various sensors, data warning thresholds, and grazing area division rules.

[0082] It should be noted that 本发明The data acquisition module uses a variety of sensors to comprehensively collect pasture-related data, providing a rich and accurate information foundation for subsequent management. The data transmission module employs encryption and error correction technologies, combined with dynamic communication protocol selection, to ensure secure, complete, and efficient data transmission. The data processing module cleans and stores data and, using machine learning algorithms, analyzes environmental and livestock data. This not only accurately predicts forage growth and identifies livestock anomalies, but also generates scientific management strategies and early warning information. The decision-making and control module makes decisions based on preset rules and algorithms, automatically controlling irrigation equipment, providing timely livestock health alerts, and rationally planning grazing areas and schedules, thus achieving automated and intelligent pasture management. The equipment control module precisely controls various pasture equipment, further enhancing management accuracy. The user interaction module provides a visual interface, allowing users to view pasture conditions in real time, manually and remotely control equipment, and adjust system parameters, enhancing user autonomy and convenience. Overall, this system improves grassland resource utilization efficiency, reduces livestock breeding risks, and reduces labor costs, promoting the development of intelligent and scientific pasture management.

[0083] The smart grassland grazing management method based on the Internet of Things in this embodiment includes:

[0084] Use sensors to collect pasture-related data and send the data to the data transmission module through the wireless communication network;

[0085] Transmitting the data collected by the data acquisition module to the data processing module;

[0086] The server receives data from the data transmission module, and the data processing module pre-processes the data to obtain management strategies and early warning information;

[0087] Based on the management strategies and early warning information generated by the data processing module, decisions are made according to preset rules and algorithms;

[0088] Provides a visual operation interface, users log in to the system through terminal devices and manage system parameter settings and rule adjustments.

[0089] This embodiment further provides a computing device applicable to a grassland intelligent grazing management system based on the Internet of Things, including:

[0090] Memory and processor; the memory is used to store computer-executable instructions, and the processor is used to execute computer-executable instructions to implement the grassland intelligent grazing management system based on the Internet of Things as proposed in the above embodiment.

[0091] This embodiment further provides a storage medium on which a computer program is stored. When the program is executed by a processor, the intelligent grassland grazing management system based on the Internet of Things proposed in the above embodiment is implemented.

[0092] The storage medium proposed in this embodiment and the implementation of the IoT-based grassland intelligent grazing management system proposed in the above embodiment belong to the same inventive concept. For technical details not fully described in this embodiment, please refer to the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0093] Through the above description of the implementation methods, those skilled in the art can clearly understand that the present invention can be implemented with the help of software and necessary general-purpose hardware, and of course it can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as a computer's floppy disk, read-only memory (ROM), random access memory (RAM), flash memory (FLASH), hard disk or optical disk, etc., including a number of instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute the methods of various embodiments of the present invention.

[0094] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. An intelligent grassland grazing management system based on the Internet of Things, characterized in that: include: The data acquisition module uses sensors to collect ranch-related data and sends the data to the data transmission module through a wireless communication network; A data transmission module, which transmits the data collected by the data acquisition module to the data processing module; The data processing module includes a server and a data processing module. The server receives data from the data transmission module, and the data processing module pre-processes the data to obtain management strategies and early warning information; The decision-making and control module receives the management strategies and warning information generated by the data processing module and makes decisions based on preset rules and algorithms; The user interaction module provides users with a visual operation interface. Users log in to the system through terminal devices and manage the system's parameter settings and rule adjustments.

2. The Internet of Things-based grassland intelligent grazing management system according to claim 1, characterized in that: The data acquisition module uses sensors to collect pasture-related data and sends the data to the data transmission module through a wireless communication network. It includes: Sensors are used to collect soil moisture data, light intensity and duration, pasture temperature, air quality, livestock location and activity trajectory, and pasture forage-related data.

3. The Internet of Things-based grassland intelligent grazing management system according to claim 1 or 2, characterized in that: The data transmission module transmits the data collected by the data acquisition module to the data processing module, including: After the data transmission module receives various types of data from the data acquisition module, it uses the AES algorithm to encrypt the data to prevent the data from being stolen or tampered with; Use data error correction technology to verify the transmitted data. If the data is found to be erroneous or lost, retransmit it. Dynamically select the appropriate communication protocol and transmission method based on network conditions and data volume.

4. The Internet of Things-based grassland intelligent grazing management system according to claim 3, characterized in that: The data processing module includes a server and a data processing module. The server receives data from the data transmission module. The data processing module pre-processes the data to obtain management strategies and early warning information, including: After the server receives the data transmitted by the data transmission module, it cleans the data through the data processing module to remove duplicate, erroneous and invalid data, stores the cleaned data in the database, and establishes historical data records; Based on soil moisture data, light intensity and duration, pasture temperature, historical data, and weather forecast information, machine learning algorithms are used to analyze the changing trends of pasture ecological environments and predict forage growth. Analyze livestock activity patterns, group distribution, and health status based on their location and activity trajectories, and use machine learning models to identify abnormal livestock behaviors and health issues. Based on the analysis results, corresponding management strategies are generated, warning thresholds for various types of data are set, and warning information is generated when the data exceeds the threshold.

5. The Internet of Things-based grassland intelligent grazing management system according to claim 4, characterized in that: The decision-making and control module receives the management strategies and warning information generated by the data processing module and makes decisions based on preset rules and algorithms, including: After receiving the management strategies and warning information from the data processing module, the decision-making and control module compares and analyzes them with the preset rules and algorithms; If the soil moisture is lower than the preset irrigation threshold, the decision and control module automatically sends an open command to the irrigation equipment to perform irrigation operations; if the soil moisture reaches the appropriate range after irrigation for a period of time, a close command is sent; When livestock show abnormal health conditions, the decision-making and control module will promptly send an alarm message to the ranch manager's terminal device; Based on forage growth and livestock distribution, the decision-making and control module rationally plans grazing areas and times, and guides livestock to appropriate grazing areas by controlling the opening and closing of fence equipment. Dynamically adjust grazing time according to the grass growth conditions in different areas.

6. The Internet of Things-based grassland intelligent grazing management system according to claim 5, characterized in that: Also includes: The equipment control module is connected to various equipment in the ranch, receives control instructions from the decision and control module, and controls the equipment; The equipment control module controls the sprinkler switch, water flow rate and irrigation time of the irrigation equipment according to the instructions of the decision and control module; controls the opening and closing of the fence equipment to limit or guide the range of livestock activities.

7. The Internet of Things-based grassland intelligent grazing management system according to claim 6, characterized in that: The user interaction module provides users with a visual operation interface. Users log in to the system through terminal devices and manage system parameter settings and rule adjustments, including: On the operation interface, users can view the ranch's environmental data, livestock location and health information, and system-generated management strategies and early warning information in real time; Displaying ranch data in the form of a map allows users to quickly understand the actual situation of the ranch; Users manually input commands through the interface to remotely control irrigation equipment, fencing equipment, etc., set the collection time intervals of various sensors, data warning thresholds, and grazing area division rules.

8. A method for a grassland intelligent grazing management system based on the Internet of Things, characterized in that: include, Use sensors to collect pasture-related data and send the data to the data transmission module through the wireless communication network; Transmitting the data collected by the data acquisition module to the data processing module; The server receives data from the data transmission module, and the data processing module pre-processes the data to obtain management strategies and early warning information; Based on the management strategies and early warning information generated by the data processing module, decisions are made according to preset rules and algorithms; Provides a visual operation interface, users log in to the system through terminal devices and manage system parameter settings and rule adjustments.

9. An electronic device comprising: memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, the steps of the grassland intelligent grazing management system based on the Internet of Things as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing computer-executable instructions, wherein the computer-executable instructions, when executed by a processor, implement the steps of the grassland intelligent grazing management system based on the Internet of Things as described in any one of claims 1 to 7.

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