[0040] In order to have a clearer understanding of the technical features, objectives and effects of the present invention, specific embodiments of the present invention will now be described with reference to the accompanying drawings.
[0041] The present invention provides an agricultural product dynamic quality monitoring system, which is characterized in that the agricultural product quality tracking system includes a sensor network, a transmission node, a local server, a cloud platform, and a user terminal;
[0042] The sensor network, transmission node, local server, cloud server, and user terminal are connected in sequence;
[0043] The sensor network includes several sensors, which are configured to capture growth data and environmental data during the growth of agricultural products,
[0044] The transmission node is configured to receive signals from sensors and perform preprocessing;
[0045] The local server is configured to acquire, store and forward sensor data, and information input;
[0046] The cloud platform is configured to store sensor data;
[0047] The user terminal is configured to monitor the quality of agricultural products according to the input information.
[0048] Preferably, the sensors in the sensor network are all wireless sensors, and the transmission node is a wireless transmission node.
[0049] Preferably, each sensor adopts a specific wireless transmission mode, and the preprocessing of the wireless transmission node includes:
[0050] 1) Verification and reception of sensor data, judging whether the data originated from the set sensor, if not, discard it;
[0051] 2) Non-linear correction of sensor data;
[0052] 3) Buffer the corrected data and package and send it regularly;
[0053] Preferably, the wireless transmission node can perform adaptive selection object transmission. When the communication between the wireless node and the local server is normal, the local server is selected as the transmission object. When the communication between the wireless node and the local server is abnormal, the nearest The wireless node serves as the transmission object.
[0054] Before the data is sent, the wireless transmission node first judges whether it contains the data of other wireless transmission nodes, and if it does, it sends it at the same time; if it does not, it only sends its own data.
[0055] Preferably, when the communication between the wireless node and the local server is abnormal, it can also be cached first, and then sent after the communication is normal.
[0056] Preferably, the system further includes a camera configured to monitor real-time images of the production process of agricultural products, and the camera is connected to a local server.
[0057] Preferably, the camera can also be configured to monitor pests.
[0058] Preferably, the local server can also be configured to input agricultural operation information, store the agricultural operation information locally, and upload it to a cloud platform.
[0059] Preferably, the agricultural operation information includes the corresponding agricultural operation, time period, geography, and area, and the agricultural operation includes at least one of the following operations: sowing, reseeding, fertilizing, irrigation, pest control .
[0060] The operation can be one type or multiple types, which will not be repeated here.
[0061] Preferably, when the cloud platform detects the input of the agricultural operation information, it will retrieve the video information corresponding to the time and the corresponding area at the same time to recognize the image, and if the recognition result is related to the input data, the data is accepted and stored; If the recognized result has nothing to do with the input result, the corresponding data will be temporarily stored in the cache database and automatically submitted to the system administrator for human judgment.
[0062] Preferably, the terminal touch control is used to control the remote surveillance camera. Operate up, down, left, and right on the screen, and the camera will follow the movement; use two fingers on the screen to expand to both outer sides at the same time to enlarge the display. At this time, the focal length of the camera changes , To make the shooting range larger; use two fingers on the screen to move to the two inner sides at the same time to reduce the display. At this time, the focal length of the camera changes to enlarge the shooting object to make it clearer.
[0063] Preferably, the user terminal can obtain historical data or real-time data that needs to be queried through an APP or a website.
[0064] For the data to be queried, it can be displayed in the form of a curve, a table, or separately.
[0065] Preferably, the sensor network includes several sensors, the sensors including pesticide sensors, heavy metal sensors, atmospheric temperature and humidity sensors, soil temperature and humidity sensors, soil tension sensors, soil EC value sensors, illuminance monitoring sensors, CO2 concentration sensors, O2 concentration Sensors, soil pH sensor, water quality pH sensor, soil salinity sensor, water dissolved oxygen sensor, electrical conductivity sensor, pest sensor, weather sensor.
[0066] Preferably, the sensor network may include one sensor or multiple sensors. I will not list them all here.
[0067] Preferably, the cloud platform includes a quality evaluation module, which can evaluate the quality of agricultural products according to the value of the sensor;
[0068] The evaluation basis of the quality evaluation module of the agricultural product quality tracking system also involves the sun exposure time, the temperature difference between day and night, and the production cycle; the specific method of the quality evaluation algorithm is that the calculation method of the quality index M is:
[0069]
[0070] Where t j Is the sunshine time on day j, T jd , T jn Are the day and night temperature on day j, k i Is the coefficient, s ji Is the measured value of the i-th sensor, and T is the growth period.
[0071] In addition, the camera can also be used to detect pests and diseases, use the local server or cloud platform for image analysis and processing, determine the proportion of the area of pests and diseases to healthy areas, and determine the degree of pests and diseases. The degree of pests can be defined as The absolute value and ratio of the difference between the area and the healthy area.
[0072] Preferably, when diseases and insect pests are considered, the calculation method of the quality index M is:
[0073] Where I j The degree of pests and diseases.
[0074] Preferably, for the present invention, the data of the current sensor network can also be combined to predict the finished product. For sensor data that is not available in the later stage of production, the method of data complement can be used, and the similarity algorithm can be used to capture the historical data and the current sensor. The data with the most similar data, take the sensor data in the subsequent period as hypothetical test data, and add it to the current sensor data to predict the finished product, such as yield, sugar content, etc.
[0075] The prediction can be implemented on a local server or on a cloud platform.
[0076] It should be noted that for the foregoing method embodiments, for the sake of simple description, they are all expressed as a series of action combinations, but those skilled in the art should know that this application is not limited by the described sequence of actions. Because according to this application, certain steps can be performed in other order or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and units involved are not necessarily required by this application.
[0077] In the above-mentioned embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in an embodiment, reference may be made to related descriptions of other embodiments.
[0078] A person of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing relevant hardware through a computer program. The program can be stored in a computer readable storage medium. When executed, it may include the procedures of the above-mentioned method embodiments. Wherein, the storage medium can be a magnetic disk, an optical disk, ROM, RAM, etc.
[0079] The above-disclosed are only preferred embodiments of the present invention. Of course, the scope of rights of the present invention cannot be limited by this. Therefore, equivalent changes made according to the claims of the present invention still fall within the scope of the present invention.
