CN116739216A - Garden operation management system and method based on Internet of things - Google Patents
Garden operation management system and method based on Internet of things Download PDFInfo
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Abstract
The invention relates to a garden job management system, in particular to a garden job management system and method based on the Internet of things. The system is characterized in that the garden operation equipment is provided with an Internet of things sensor, and each Internet of things node corresponds to one or more garden operation equipment and is connected to the data storage and analysis processing system through a wireless network; the data storage and analysis processing system analyzes and processes the uploaded data and feeds the data back to the node of the Internet of things to intelligently control the garden operation equipment; the garden job management system based on the Internet of things is particularly important, promotes the intellectualization of garden jobs, emphasizes the wide application of the intellectualization technology in the aspect of garden job management through big data and artificial intelligence, and enables the garden job management to be more scientific and accurate.
Description
Technical Field
The invention relates to a garden job management system, in particular to a garden job management system and method based on the Internet of things.
Background
At present, the traditional garden operation management mode mainly relies on manual inspection and management, and comprehensive monitoring and real-time treatment of garden operation conditions are difficult to achieve. Meanwhile, the efficiency of manual inspection is low, all-weather monitoring is difficult to achieve, and the method often brings a lot of trouble to a manager in garden production management. The garden operation management based on the Internet of things is a novel management mode for modern garden operation, the data of a garden operation site is collected by utilizing the Internet of things technology, the garden operation process is monitored and predicted in real time, and a decision support and optimization scheme is provided through a data analysis and prediction model. The technology combines advanced technologies such as the Internet of things, big data, cloud computing and artificial intelligence, integrates various components such as the Internet of things sensor, the data acquisition node, the cloud platform and the mobile client, can greatly improve the efficiency and quality of garden operation, and simultaneously reduces the cost and the manpower input of the garden operation. However, in the current garden operation management system based on the internet of things, there are some short boards or disadvantages:
1. data quality problem: although existing sensor technologies and data processing methods of the internet of things are becoming more mature and popular, some data quality problems still exist. Such as data noise, data loss, data misalignment, etc., which directly affects the reliability and practicality of the system. For a garden job management system based on data, the data is a key factor, and the problem of data quality needs to be solved. 2. System safety hidden trouble in the garden operation management system based on the internet of things under the relatively open internet environment faces the problems of data safety hidden trouble such as data leakage, hacking attack, phishing and the like. At present, many enterprises and institutions have studied about the security problem of the internet of things, but more technologies and practical verification are required for absolute guarantee. 3. The functional requirements are not enough: at present, a general garden work management system based on the Internet of things does not realize core function requirements, such as automatic monitoring, automatic inspection, automatic fault processing and the like, and the realization of the functions requires the support of corresponding machine learning, image processing, artificial intelligence and other technologies. 4. The operation is complex: the existing garden work management system based on the Internet of things is relatively low in usage amount, so that a small number of short boards exist in the aspects of operation, application and popularization, for example, compared with a traditional garden management method, the garden work management system still is complex, and a user beginner threshold is high. 5. The system is not integrated enough: at present, many garden operation management systems based on the Internet of things adopt a mode of separating hardware from software, operate independently of each other, lack unified integration standards and data formats, and influence data communication and operation efficiency of the system.
Disclosure of Invention
The invention aims to provide a garden operation management system and method based on the Internet of things, so as to solve part of the problems in the background technology.
The invention solves the technical problems as follows: the garden operation management system based on the Internet of things comprises garden operation equipment, internet of things nodes, a data storage and analysis processing system and an information acquisition and processing method of the Internet of things equipment, and is characterized in that the garden operation equipment is provided with an Internet of things sensor, and each Internet of things node corresponds to one or more garden operation equipment and is connected to the data storage and analysis processing system through a wireless network; the data storage and analysis processing system analyzes and processes the uploaded data and feeds the data back to the node of the Internet of things to intelligently control the garden operation equipment;
further, the garden working equipment is a water sprayer, a spray irrigation controller, electric gardening scissors and other garden working equipment except examples; the data storage and analysis processing system analyzes and processes the uploaded data; a user interface is arranged in the data storage and analysis processing system, and state inquiry and remote control are carried out on the garden operation equipment;
A garden job management method based on the Internet of things comprises the following steps:
a. installing an Internet of things sensor on garden operation equipment;
b. constructing an Internet of things node, and connecting the Internet of things node to a data storage processing system through a wireless network;
c. the data storage and analysis processing system analyzes and processes the uploaded data to obtain a garden operation condition, and intelligently controls the garden operation equipment according to the processing result;
d. providing a user interface, wherein the user interface can monitor the state of the garden operation in real time, and a manager can check the state of the garden operation equipment on the user interface, control the operation of the garden operation equipment in real time and manage the operation state of the garden operation equipment;
further, the sensor node of the Internet of things acquires the running state and the operation information of the equipment in real time and sends the running state and the operation information to the transmission module of the Internet of things through the radio module; and the internet of things transmission module is used for gathering the data received from all the sensor nodes and transmitting the data to the data storage and analysis processing system for processing.
Further, the data storage and analysis processing system is composed of the following modules:
(1) Database module: the method comprises the steps of storing data uploaded by a sensor node of the Internet of things;
(2) And a data preprocessing module: preprocessing the data uploaded by the sensor to remove invalid data and abnormal data;
(3) And a data mining analysis module: the core module is used for analyzing the data acquired from the preprocessing module;
(4) Decision instruction module: according to the data analysis result, intelligent control is carried out on the garden operation equipment, and corresponding adjustment is carried out;
(5) A user interface module: the module provides a user interface, which is convenient for a manager to monitor and manage the garden operation state in real time.
Further, the flow of the information acquisition and processing of the internet of things equipment is as follows:
(1) And (3) data acquisition: sensors on the device monitor the environment and device status, convert analog signals to digital signals through analog-to-digital converters, and the digital signals are received by the processor;
(2) And (3) data processing: the processor filters, cuts and processes the acquired data, converts the digital signals into data frames or data packets and transmits the data frames or data packets to the physical layer;
(3) And (3) data transmission: and transmitting the data packet to a cloud server through a wireless communication module.
Further, the functions of the one or more sensor nodes corresponding to the one or more garden working devices are realized by the following operations:
(1) Configuring sensor node information;
(2) Establishing a corresponding relation of the equipment sensors;
(3) Monitoring data in real time and analyzing and processing the data;
(4) Device control and management;
the method for establishing the corresponding relation between the sensor and the garden operation equipment comprises the following steps:
(1) Based on physical location: the sensors are corresponding to the garden operation equipment according to the physical positions, so that the monitoring range of each sensor is ensured to be matched with the operation requirement of the equipment;
(2) Based on device type and attributes: establishing a corresponding relation between equipment and a sensor according to the type and the attribute of the garden operation equipment;
(3) Based on the operating mode and sampling frequency: when the association relation between the sensor and the garden working equipment is not clear, the corresponding garden working equipment is determined according to the characteristics of the working mode, the sampling frequency, the precision and the like of the sensor.
Further, the data storage and analysis processing system analyzes and processes the uploaded data in the following manner:
(1) And (3) data acquisition: uploading the data to a cloud end through an Internet of things node;
(2) And (3) cleaning data: processing the useless data through data cleaning, wherein the useless data comprise abnormal values, invalid values, repeated values and the like;
In the above steps, the data cleaning adopts the following steps:
(2.1), data preprocessing: preliminary processing is carried out on the original data;
(2.2), abnormal data detection: detecting abnormal data of the processed data, and finding out noise and outliers in the data; and the detected abnormal value is selected to be deleted, replaced or interpolated;
(2.3), data deduplication: performing deduplication processing on the repeated data, and guaranteeing the data uniqueness in the whole system;
(2.4), data accuracy verification: on one hand, repeated measurement values of the sensor are used, and on the other hand, a formula or a model is utilized to check the sensor data;
(3) And (3) data integration: integrating the acquired data into a data table, and normalizing, standardizing and normalizing the data to prepare for subsequent analysis;
(4) And (3) data statistical analysis: trend analysis, anomaly detection, association analysis and classification cluster analysis are carried out on the integrated data through a big data analysis technology;
(5) Machine learning model training and application: predicting the state and abnormal indexes of garden operation equipment, and predicting equipment faults in advance;
(6) Visualization of data: the statistical analysis results are visually displayed in the forms of icons, tables and the like, so that an administrator can conveniently know the state and the management condition of the garden operation equipment;
the mode of feeding back the decision result to the node of the internet of things can be realized by the following modes:
(1) Feedback via cloud platform: the data storage and analysis processing system feeds back an analysis result to the node of the Internet of things through the cloud platform and issues a corresponding instruction;
(2) Feedback through the local management platform: the management platform controls the node of the Internet of things, feeds the analyzed and processed data back to the management platform, generates corresponding management operation and sends the management operation to the node of the Internet of things.
Further, the intelligent control method for the garden operation equipment comprises the following steps:
(1) Controlling the working state of the garden working equipment: after the node of the Internet of things receives the feedback data, different garden operation requirements can be met by controlling the working state of the garden operation equipment;
(2) Parameter setting for controlling garden operation equipment: aiming at different garden operation equipment, different operation requirements are met by controlling equipment parameters.
Further, the internet of things sensor includes:
(1) Temperature sensor: the temperature state monitoring device is used for monitoring the temperature state of the garden operation equipment in real time;
(2) Humidity sensor: the system is used for monitoring the humidity state of the garden operation equipment in real time;
(3) Illumination intensity sensor: the system is used for monitoring the illumination state of the garden operation equipment in real time;
(4) CO2 sensor: the system is used for monitoring the concentration of CO2 in the garden operation equipment in real time;
(5) Water quality sensor: the water quality monitoring device is used for monitoring the water quality in the garden operation equipment in real time.
The invention has the beneficial effects that:
1. the operation efficiency is improved: the garden operation management system based on the Internet of things monitors and predicts the garden operation process in real time, provides a decision support and optimization scheme, can effectively improve the efficiency of garden operations such as chemical, irrigation and pruning, and reduces the manpower investment and management cost.
2. Optimizing the operation quality: along with the development of technology and the improvement of data precision, the garden work management system based on the Internet of things can monitor and evaluate the garden work quality in time, discover hidden danger and problems, correct and adjust in time and optimize the work quality.
3. The job management cost is reduced: the garden job management system is integrated, so that job management and coordination are optimized, and waste of manpower and material resources and unnecessary cost are reduced. According to scientific operation deployment of garden operation, the management cost can be effectively reduced to the minimum.
4. Enhancing the operation safety: garden operation management system based on thing networking can effectively ensure garden operation safety through the various data monitoring such as early warning mode, equipment fault diagnosis, operation scene monitoring, avoids the emergence of garden operation accident.
5. Intelligent garden operation is advanced: the garden job management system based on the Internet of things is particularly important, promotes the intellectualization of garden jobs, emphasizes the wide application of the intellectualization technology in the aspect of garden job management through big data and artificial intelligence, and enables the garden job management to be more scientific and accurate.
In conclusion, the garden job management system and method based on the Internet of things have important significance and beneficial effects on intelligent and sustainable development of garden jobs, improvement of job efficiency, quality and safety, optimization of resource management results.
Drawings
Fig. 1 is a flowchart of a garden job management system based on the internet of things.
FIG. 2 is a partial flow chart of the data storage and analysis processing system of the present invention.
Description of the embodiments
The following describes the embodiments of the present invention in detail with reference to the drawings.
Examples: a garden operation management system based on the Internet of things comprises garden operation equipment, internet of things nodes, a data storage and analysis processing system and an Internet of things equipment information acquisition and processing method, wherein the Internet of things sensors are installed on the garden operation equipment, and each Internet of things sensor node corresponds to one or more garden equipment and is connected to the data storage and analysis processing system through a wireless network; the data storage and analysis processing system analyzes and processes the uploaded data and feeds the data back to the node of the Internet of things to intelligently control the garden equipment;
The garden operation equipment is a water sprayer, a spray irrigation controller and electric gardening scissors, and the garden operation equipment except examples is also included; the data storage and analysis processing system performs analysis processing on the uploaded data and performs intelligent control on the garden equipment based on the processing result; the data storage and analysis processing system is provided with a user interface so that a manager can monitor the state of garden operation in real time and perform state inquiry and remote control on garden equipment;
a garden job management method based on the Internet of things comprises the following steps:
a. installing an Internet of things sensor on garden operation equipment;
b. constructing an Internet of things node, and connecting the Internet of things node to a data storage processing system through a wireless network;
c. the data storage and analysis processing system analyzes and processes the uploaded data to obtain a garden operation condition, and intelligently controls garden equipment according to a processing result;
d. providing a user interface, monitoring the operation state of the garden in real time, checking the state of the garden equipment on the user interface by a manager, controlling the operation of the garden equipment in real time, and managing the operation state of the garden equipment;
the sensor node of the Internet of things can acquire the running state and the operation information of the equipment in real time and send the running state and the operation information to the transmission module of the Internet of things through the low-power-consumption radio module; the internet of things transmission module can collect data received from all the sensor nodes together and transmit the data to the data storage and analysis processing system for processing; the system can also carry out remote monitoring and management through user interfaces such as a mobile phone APP or a webpage end and the like;
In a specific implementation, the sensor node can adopt various physical quantity sensors, such as an illumination sensor, a humidity sensor, a temperature sensor, a soil humidity sensor, a pressure sensor and the like; the real-time data collected by the sensor can be used for calculating the working state of each garden equipment by the following formula:
the real-time monitoring value is a real-time value collected from a sensor node on the garden equipment, the theoretical value is a value range which is obtained by presetting, experience or theoretical calculation and is reached by the equipment, for example, in the watering operation, the theoretical value is watering when the soil humidity reaches a certain value, and the specific value range can be set according to factors such as different plant types, climate conditions and the like;
the system is used for analyzing and processing data based on monitoring data of the sensor, and sending an instruction to control corresponding equipment to adjust to a theoretical state after a problem is found; the specific adjustment mode can be set according to different garden equipment and operation conditions;
through a user interface of the data storage and analysis processing system, a manager can monitor the operation state of gardens in real time, manage the operation state and the running state of garden equipment and perform remote control;
The data storage and analysis processing system can also analyze and predict the monitoring data through technologies such as a machine learning algorithm, and the like, so that the influence caused by the change of a planting structure or the environment is found in advance, the quality of garden operation is improved, for example, aiming at the abnormal death of 1290 plants, the types of affected plants can be predicted, and rescue or nutrition optimization measures are carried out in advance, so that the loss is avoided;
therefore, the garden operation management system of the Internet of things improves the garden operation efficiency and precision through automatic and intelligent management, reduces the waste of manpower and material resources, greatly saves the management cost, and has obvious effects in actual use;
the data storage and analysis processing system consists of the following modules:
(1) Database module: the system comprises a data storage module, a data analysis module and a data analysis module, wherein the data storage module is used for storing data uploaded by a sensor node of the Internet of things and providing an interface for data query and statistical analysis;
(2) And a data preprocessing module: the module is mainly used for preprocessing the data uploaded by the sensor and removing invalid data and abnormal data; in the preprocessing process, algorithms such as smooth filtering, median filtering, sliding average and the like can be adopted, so that the data is more accurate;
(3) And a data mining analysis module: the module is a core module for analyzing the data acquired from the preprocessing module, mainly adopts data mining technologies such as a machine learning algorithm, a statistical method and the like, trains and analyzes the data uploaded by the sensor, extracts characteristic information and forms a certain model; these models can predict the status of the forest apparatus in a future period of time, such as the time opportunity for watering or fertilizing, etc.;
(4) Decision instruction module: the module can intelligently control the garden equipment according to the data analysis result, and correspondingly adjust, for example, adjust the sprinkling irrigation controller, so that the sprinkling irrigation quantity is adjusted along with the change of weather conditions, the garden operation efficiency is improved, and the waste is reduced;
(5) A user interface module: the module provides a user interface, is convenient for a manager to monitor and manage the garden work state in real time, inquire and remotely control the state of the garden equipment, and check analysis and prediction results;
in a specific implementation, the data preprocessing module in the data storage and analysis processing system adopts the following algorithm:
1. smoothing filter algorithm:
2. median filtering algorithm:
Wherein, the liquid crystal display device comprises a liquid crystal display device,representing the original data +.>Representing the filtered data;
the data mining analysis module adopts various machine learning algorithms, such as linear regression, support vector machine, naive Bayes, neural network and the like, so as to establish a model for data prediction and monitoring;
finally, the decision instruction module intelligently controls the garden equipment through the technologies of self-adaptive control theory, fuzzy control and the like, so that the garden operation efficiency is improved and the waste is reduced;
in a specific implementation, the user interface module of the data storage and analysis processing system may construct a web interface by applying a front-end technology, such as HTML, CSS, javaScript, or develop a mobile phone APP; the interface may provide the following functions:
(1) Monitoring and displaying the garden operation state in real time, including the real-time operation state, operation time and the like of the garden equipment;
(2) The system can provide the state inquiry and remote control functions of garden equipment, for example, the system can control equipment such as a sprinkler, a sprinkling irrigation controller, gardening scissors and the like, and adjust parameters of the equipment such as watering time, irrigation area and the like;
(3) Checking the data analysis and prediction report so that the manager can know the condition of the whole garden operation and make further decisions;
(5) Issuing an alarm and informing abnormal conditions, such as reminding abnormal conditions of operation states of garden equipment, equipment faults and the like;
specifically, the user interface module can be implemented by using various front end frameworks to realize functions such as dynamic data display, real-time interaction and the like; for example:
(1) When the real-time running state of the garden equipment is displayed, using a constant-speed animation or an animation () method of jQuery to enable elements to smoothly move within a certain time, so that a dynamic effect is realized;
(2) The user interface can also visualize the data through an open source chart library, a graphic library and the like, for example, the display and the comparison of garden operation data are realized through Echarts;
(3) Transmitting a real-time data request through Ajax, assuming that the backend service address is '/api/realtem-data', this can be:
javascript
setInterval(()=>{
$.ajax({
url:'/api/realtime-data',
success:function(data){
$('.realtime-data').text(data);
}
});
},3000);
here, the scheme is that an Ajax request is sent once in 3 seconds;
through the technical means, a user interface module of the data storage and analysis processing system can provide convenient and quick operation experience and assist management personnel to make garden operation management decisions;
the information acquisition and processing of the equipment of the Internet of things are key links for realizing various applications; an internet of things device is generally composed of an embedded device, a sensor, a wireless communication module and the like; the data acquisition and transmission process comprises the following steps:
(1) And (3) data acquisition: sensors on the device monitor the environment and device status, converting analog signals to digital signals through an analog-to-digital converter (ADC), the digital signals being received by the processor;
(2) And (3) data processing: the processor filters, cuts and processes the acquired data, converts the digital signals into data frames or data packets and transmits the data frames or data packets to the physical layer;
(3) And (3) data transmission: transmitting the data packet to a cloud server through a wireless communication module;
in terms of acquisition and processing composition of device information, the following techniques may be employed:
(1) Internet of things communication protocol: the internet of things communication must be based on commonly accepted standardized protocols, including MQTT, HTTP, AMQP and COAP, etc., which both provide data transmission options and security guarantees; the internet of things protocol is defined and standardized according to application scenarios, and the protocols can interoperate;
(2) Sensor and wireless communication module: different sensors can select different communication modes and data acquisition modes according to the design principle, application purposes and environmental requirements; for example, some common wireless communication methods include WiFi, BLE, zigBee, loRa; meanwhile, factors such as precision, power consumption, data transmission quantity, fault tolerance and the like are also required to be considered when the sensor is selected;
(3) Edge calculation: the internet of things equipment has the characteristics of calculation and communication capability, and can be calculated and processed by utilizing an edge calculation technology; the edge calculation can process the local data of the equipment, and forwards the data to the data center according to factors such as hit rate, network delay and the like, thereby having a certain effect on reducing data transmission and improving data processing performance;
(4) Big data and machine learning: big data and machine learning technology can rapidly analyze and process a large amount of data acquired by the sensor; various analysis, modeling and prediction are carried out through a data analysis processing system, and the dimensions such as equipment state, production efficiency and the like are evaluated, so that a decision is developed;
therefore, by utilizing the technical means, various physical quantities can be converted into digital data readable by the equipment, the digital data are communicated, and the data are uploaded to a cloud for analysis; meanwhile, on the basis of utilizing big data and machine learning technology, the scheme can completely analyze the data, form a data mode, and finally accurately and structurally transcribe and analyze the equipment monitoring data to realize the connection of equipment-cloud;
in garden equipment monitoring, in order to better control and manage different equipment, the function of one or more sensor nodes corresponding to one or more garden equipment can be realized by binding each Internet of things sensor with the garden equipment; specifically, the scheme can be realized by the following operations:
(1) Configuration sensor node information: when the sensors of the Internet of things are installed and deployed, corresponding information such as numbers, sensor types, positions, action ranges and the like needs to be configured for each sensor node; the information can be realized by means of manual input, code table correspondence or scanning of two-dimensional codes and the like;
(2) Establishing a corresponding relation of the device sensor: through one sensor node, the scheme can correspond to one or more garden equipment, and a corresponding relation of the equipment sensors is established; when the corresponding relation is established, the type and the monitoring range of the sensor and the operation requirement and the corresponding relation of the equipment are mainly considered; for example, in a garden management system, one air temperature and humidity sensor can simultaneously correspond to a plurality of humidifiers, and precise control is realized;
(3) Monitoring data in real time and carrying out data analysis processing: after the corresponding relation of the equipment sensors is established, the sensor data can be monitored in real time; analyzing, excavating and predicting the data uploaded by the sensor through a cloud big data processing system, and calculating relevant equipment monitoring indexes; the scheme can carry out remote control and management operation on the garden equipment through the calculated index;
(4) Device control and management: the scheme can conveniently realize the equipment control and management functions through the terminal user interface; through the terminal user interface, a user can know the state and monitoring condition of the equipment in real time and operate and control the equipment so as to improve the efficiency of garden operation and ensure the safety of the equipment;
through the above operation, it may be achieved that one or more sensor nodes correspond to one or more garden devices; the fine-granularity monitoring and controlling scheme can better improve the efficiency and the safety of the garden equipment, realize the efficient use of resources, reduce the cost, the energy consumption and the like;
in the scheme, the corresponding relation between the sensor and the garden equipment is key; the following are some methods for establishing the correspondence:
(1) Based on physical location: the sensor can be corresponding to the garden equipment according to the physical position, so that the monitoring range of each sensor can be ensured to be matched with the operation requirement of the equipment; for example, in a garden facility monitoring system, the air quality sensor can be arranged at a key position of a garden, such as a flower bed, a tree forest and the like, the state and the change rule of the air quality around the sampling position are obtained according to the analysis sensor data, and then the working state and the parameters of the humidifier are adjusted according to the sampling result;
(2) Based on device type and attributes: according to the types and the attributes of the garden equipment, the method can establish the corresponding relation between the equipment and the sensor; for example, the temperature sensor is bound with the humidifier, and the working state and parameters of the humidifier are automatically adjusted by monitoring the changes of environmental parameters such as temperature, humidity and the like in real time so as to meet different garden operation requirements;
(3) Based on the operating mode and sampling frequency: when the association relation between the sensor and the garden equipment is not clear, the corresponding garden equipment can be determined according to the characteristics of the working mode, the sampling frequency, the precision and the like of the sensor; for example, the temperature and humidity sensor and the meteorological station are different devices, but since the characteristics of sampling frequency, precision and the like are similar, the characteristics can be corresponding to each other;
by establishing the corresponding relation of the device sensors, the method can better utilize the technology of the Internet of things to realize the omnibearing monitoring, accurate control and real-time processing of the device; the scheme can effectively improve the management and the operation efficiency of the garden equipment, help enterprises save the cost, and simultaneously can reduce the consumption of energy and environmental resources to realize sustainable garden management;
The data storage and analysis processing system is used for analyzing and processing the uploaded data in the following mode:
(1) And (3) data acquisition: in the garden operation process, a large amount of data such as temperature and humidity, illumination, moisture, wind direction, soil salinity, fertilizer proportion and the like need to be collected, and the data are uploaded to the cloud through the nodes of the Internet of things;
(2) And (3) cleaning data: due to the difference of data quality, abnormal values, invalid values, repeated values and the like can exist in the data, and the useless data are processed through data cleaning so as to ensure that the processed data are accurate and reliable;
in a garden work management system based on the internet of things, a large amount of sensor data needs to be subjected to data cleaning so as to ensure the integrity, accuracy and effectiveness of the data. The data cleaning can be performed by the following steps:
(2.1), data preprocessing: preliminary processing is performed on the raw data, such as removing useless data, converting the data into a standard format, unifying data units, and the like.
(2.2), abnormal data detection: and detecting abnormal data of the processed data, and finding out noise and outliers in the data. The anomaly detection of the data may be performed using a statistical method, a data mining method, a machine learning method, or the like. The detected outlier may be selected for deletion, replacement, or interpolation.
(2.3), data deduplication: because the sensor data in the device can be repeatedly uploaded or updated, repeated data is required to be subjected to de-duplication processing, and the data uniqueness in the whole system is ensured.
(2.4), data accuracy verification: verifying the accuracy of data can generally be done from two aspects, on the one hand using repeated measurements of the sensor and on the other hand using a formula or model to verify the sensor data, for example, the data uploaded to the temperature sensor can be verified using a formula, such as (T x 1.8) +32, converting degrees fahrenheit to degrees celsius, and can be compared with the data measured by the sensor to check the accuracy of the data.
(2.5), data visualization: through a data visualization mode, the cleaned data can be intuitively presented in a chart form, and a user can conveniently analyze and process the data. For example, the data after the accuracy processing is visually displayed in real time by using data analysis software, a dashboard and the like.
The method is a general flow for data cleaning in the garden job management system based on the Internet of things, the data cleaning is a key step for improving the data precision and reliability, the value and quality of the data can be improved through an effective data cleaning method, and effective supervision and optimization decision of garden job management are realized.
(3) And (3) data integration: integrating the acquired data into a data table, and normalizing, standardizing and normalizing the data to prepare for subsequent analysis;
(4) And (3) data statistical analysis: the garden operation management system performs trend analysis, anomaly detection, association analysis, classification cluster analysis and the like on the integrated data through a big data analysis technology so as to realize real-time judgment and processing on equipment states, anomaly indexes and the like; for example, the soil moisture data is statistically analyzed, whether the soil moisture is enough or not is judged, the water-fertilizer ratio is controlled, and the quality of lawns, flower beds and nursery is improved;
(5) Machine learning model training and application: machine learning techniques are often used in such systems for prediction, classification, and clustering; by analyzing the historical data, the state, abnormal indexes and the like of the garden equipment can be predicted, equipment faults can be predicted in advance, and the operation efficiency of the garden equipment is improved;
(6) Visualization of data: the statistical analysis results are visually displayed in the forms of icons, tables and the like, so that an administrator can conveniently know the state and the management condition of the garden equipment;
the mode of feeding back the decision result to the node of the internet of things can be realized by the following modes:
(1) Feedback via cloud platform: the data storage and analysis processing system feeds back an analysis result to the node of the Internet of things through the cloud platform and issues a corresponding instruction;
(2) Feedback through the local management platform: the management platform controls the node of the Internet of things, feeds the analyzed and processed data back to the management platform, generates corresponding management operation and sends the management operation to the node of the Internet of things;
therefore, the garden operation management system and method based on the Internet of things can realize omnibearing monitoring, accurate control and real-time processing of garden equipment through big data analysis and the Internet of things technology, and have higher management and operation efficiency;
the intelligent control method for the garden equipment comprises the following steps:
(1) Controlling the working state of the garden equipment: after the node of the Internet of things receives the feedback data, different garden operation requirements can be met by controlling the working state of the garden equipment; for example, the setting temperature of the temperature increasing device is adjusted according to the temperature value detected by the temperature sensor; for the humidifying equipment, controlling the starting and stopping of the humidifying equipment and the supply of moisture according to the change of the air humidity;
(2) Parameter setting of control garden equipment: aiming at different garden equipment, different operation requirements are met by controlling equipment parameters; for example, for the lighting equipment, parameters such as lighting intensity, color temperature, light area and the like can be set to meet photosynthesis requirements of different kinds of plants, visual safety requirements of personnel and the like;
In the two control methods, the parameter setting of the control garden equipment is realized by a mathematical model based on a control algorithm; specifically, the PID control algorithm can be adopted, and the algorithm calculates the output value of the controller in a combined mode of three parameters of proportion (P), integral (I) and derivative (D), and the output value is used as a judging basis for the working state of the equipment and parameter setting; the algorithm may be calculated by the following formula:
output=Kp*(error+1/Ti*integral+Td*derivative)
wherein Kp, ti and Td represent a proportional coefficient, an integral time constant and a differential time constant, respectively; error represents the current temperature or humidity deviation value, integral represents the integral term of the deviation value, and derivative represents the differential term of the deviation value;
in practical application, parameters of the PID control algorithm need to be adjusted according to different conditions according to different equipment and operation requirements so as to achieve the optimal control effect; the method needs to be adjusted through analysis of actual test and feedback data so as to meet specific garden operation requirements;
the thing networking sensor includes:
(1) Temperature sensor: for monitoring the temperature state of garden working equipment in real time, such as a greenhouse, a flower bed, lighting equipment, water fertilizer sprinkling irrigation equipment and the like; common temperature sensors include thermistor sensors, NTC thermistor sensors, thermocouple sensors, infrared (IR) sensors, and the like;
(2) Humidity sensor: for monitoring the humidity state of garden working equipment in real time, such as a greenhouse, a flower bed, water and fertilizer sprinkling irrigation equipment, a humidifier, ventilation equipment and the like; common humidity sensors include capacitive humidity sensors, resistive humidity sensors, pressure humidity sensors, and the like;
(3) Illumination intensity sensor: for monitoring in real time the illumination status of garden work equipment, such as lighting equipment, greenhouses, flower beds, sunlight houses, etc.; common illumination intensity sensors include photodiode sensors, photoresistor sensors, solar panel sensors, and the like;
(4) CO2 sensor: for monitoring in real time the concentration of CO2 in garden work equipment, such as greenhouses, flower beds, humidifiers, etc.; common CO2 sensors include Infrared (IR) sensors, electrochemical sensors, optical sensors, and the like;
(5) Water quality sensor: the water quality monitoring system is used for monitoring water quality in garden operation equipment in real time, such as water and fertilizer sprinkling irrigation equipment, a water tank, base fertilizer irrigation and the like; common water quality sensors include electrochemical sensors, fluorescence sensors, ultraviolet (UV) sensors, and the like;
the garden operation management system of the Internet of things can monitor environmental parameters, running states and water quality data in real time through the monitoring data of the sensors, so that intelligent management and optimization are carried out on garden operation equipment, and scientization and efficiency of garden operation are realized;
The layout of the sensors of the Internet of things in the garden operation management system based on the Internet of things needs to fully consider the linkage relation among various sensors, and simultaneously covers the area where the equipment is located as much as possible;
temperature sensor and humidity sensor: the two sensors typically need to be paired for use, as temperature and humidity are typically closely related; when in arrangement, the temperature sensors and the humidity sensors can be alternately arranged in an staggered mode; this allows for more comprehensive and accurate environmental parameter data to be obtained and helps to reduce errors;
illumination intensity sensor: the illumination intensity sensor is not particularly strict in layout as compared to the temperature sensor and the humidity sensor; it is usual to install according to the layout of the equipment and the actual lighting requirements, for example in the upper part or side of the greenhouse or in a suitable arrangement in an outdoor sunlight room;
CO2 sensor and water quality sensor: these two sensors generally need to be more accurately arranged to ensure accuracy of measured environmental parameters and water quality data; for example, for a water quality sensor, it is considered to be arranged in a place where water flow is concentrated, and for a CO2 sensor, it is considered to be installed in a place where air circulates, so as to better monitor the concentration of CO2 in the air;
When the sensors are arranged, linkage work between the sensors needs to be realized by means of an Internet of things system and an Internet of things node; for example, real-time operation of ventilation, irrigation and humidification systems is controlled based on the monitoring data, or early warning and alerting based on the operating conditions; meanwhile, the Internet of things system can provide related optimization suggestions through data analysis and processing, so that the efficiency and quality of garden operation are further improved;
the Internet of things node and the Internet of things sensor are important components in the garden job management system based on the Internet of things, but the functions and the roles of the Internet of things node and the Internet of things sensor are different.
1. Internet of things sensor: the internet of things sensor is a device specially used for acquiring environmental parameters and device operation state data. The sensors can measure environmental factors such as temperature, humidity, illumination intensity, CO2 concentration, water quality and the like, record the running state and the working quality of equipment, and upload the data to a cloud or an Internet of things node through the Internet of things technology.
2. The node of the Internet of things: the internet of things node is a device for managing and controlling sensor data. The functions of the intelligent monitoring system comprise that data uploaded by the sensors are collected and stored in a cloud platform, the data are analyzed and processed, intelligent reports and decision support are generated according to the data, and linkage control with other equipment, such as irrigation equipment, ventilation equipment and the like, is realized. The node of the Internet of things sends sensor data to the cloud through a wireless local area network or the Internet, and sends control instructions to garden operation equipment according to cloud instructions.
According to the garden operation management system based on the Internet of things, disclosed by the invention, the real-time monitoring and management of the garden operation process are realized by connecting sensors and equipment of the Internet of things such as the sprinkler, the sprinkling irrigation controller and the gardening scissors fittings to the Internet. The specific process is as follows:
first, sprinkler and sprinkler controllers are two main devices for adjusting parameters such as moisture, temperature, and humidity in a garden work environment. Through carrying on the thing networking sensor in sprinkler and sprinkling irrigation controller, can carry out real-time supervision and data acquisition to water spray and sprinkling irrigation operation. The data acquired by the sensor are connected to the cloud platform through the Internet of things for storage and analysis, so that water spraying and sprinkling irrigation in garden operation can be finely managed, and the frequency, the intensity and the duration of water spraying and sprinkling irrigation are automatically controlled.
Secondly, gardening scissors accessory is a device that realizes unmanned, intelligent pruning through the sensor, can intelligent pruning under the condition of not damaging the plant, realizes the automation of afforestation operation. The Internet of things sensor mounted in the accessory can sense the working state of the gardening scissors and the growth condition of plants in real time, and upload data to the cloud platform for real-time processing and analysis. The gardening scissors accessory can be connected with other devices such as a water sprayer and a spray irrigation controller, and intelligent management and supervision of plants are realized together.
By utilizing the sensor and the equipment of the Internet of things, the real situation of garden operation and cloud big data are combined, real-time monitoring and management of garden environment and plant ecology are realized, the operation efficiency and quality are improved, and finally the intelligent and scientific garden operation is promoted.
In a specific application, the gardening work management system based on the internet of things can achieve the following points.
1. Environmental monitoring is achieved through the internet of things sensor: for example, by arranging a sensor on a garden operation site, data such as ambient temperature, humidity, illumination, soil moisture and the like are collected, and the data are transmitted to a cloud service end for processing and displaying. Therefore, operators can scientifically and reasonably adjust the garden working environment according to the data analysis of the cloud service end, and the garden working is guaranteed to be beneficial to the growth and development of plants.
2. Device management is achieved through the internet of things sensor: for example, the state of garden operation equipment, such as the opening time of a water pump, the water quantity, the water temperature, the water quality and the like, is monitored through the sensor of the Internet of things, the running state of the equipment is mastered in time, and the equipment is effectively prevented from malfunctioning.
3. Plant management is achieved through the internet of things sensor: for example, through installing thing networking sensor in gardens, monitor the growth situation of various crops, judge whether to appear growing abnormally, intelligent pruning of horticulture scissors and plant maintenance to guarantee that garden crop keeps a good state, let the city more beautiful.
4. Personnel management is achieved through the Internet of things sensor: for example, by monitoring and analyzing the positioning, track, working efficiency and the like of the staff, the work distribution and task execution of the staff in the garden work are optimized, and the working efficiency and quality are improved.
Through the application, the gardening operation management system based on the Internet of things can automatically control the operation period and the operation time, fully utilize data analysis, improve the efficiency and the accuracy of gardening green operation, and reduce the management cost. The method provides a good platform for landscaping management and promotes the comprehensive development of urban landscaping engineering.
The foregoing has shown and described the basic principles, principal features and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, and that the above embodiments and descriptions are merely illustrative of the principles of the present invention, and various changes and modifications may be made without departing from the spirit and scope of the invention, which is defined in the appended claims. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (10)
1. The garden operation management system based on the Internet of things comprises garden operation equipment, internet of things nodes, a data storage and analysis processing system and an information acquisition and processing method of the Internet of things equipment, and is characterized in that the garden operation equipment is provided with an Internet of things sensor, and each Internet of things node corresponds to one or more garden operation equipment and is connected to the data storage and analysis processing system through a wireless network; the data storage and analysis processing system analyzes and processes the uploaded data and feeds the data back to the node of the Internet of things to intelligently control the garden operation equipment.
2. The system of claim 1, wherein the garden work equipment is a sprinkler, a sprinkler controller, electric gardening scissors and a garden work equipment other than an example; the data storage and analysis processing system analyzes and processes the uploaded data; and a user interface is arranged in the data storage and analysis processing system, so that state inquiry and remote control are performed on the garden operation equipment.
3. A garden job management method based on the Internet of things comprises the following steps:
a. Installing an Internet of things sensor on garden operation equipment;
b. constructing an Internet of things node, and connecting the Internet of things node to a data storage processing system through a wireless network;
c. the data storage and analysis processing system analyzes and processes the uploaded data to obtain a garden operation condition, and intelligently controls the garden operation equipment according to the processing result;
d. a user interface is provided, the state of the garden operation can be monitored in real time, a manager can check the state of the garden operation equipment on the user interface, the operation of the garden operation equipment is controlled in real time, and the operation state of the garden operation equipment is managed.
4. The garden operation management system based on the internet of things according to claim 1, wherein the sensor node of the internet of things collects the running state and the operation information of the equipment in real time and sends the running state and the operation information to the transmission module of the internet of things through the radio module; and the internet of things transmission module is used for gathering the data received from all the sensor nodes and transmitting the data to the data storage and analysis processing system for processing.
5. The garden job management system based on the internet of things according to claim 4, wherein the data storage and analysis processing system comprises the following modules:
S1, a database module: the method comprises the steps of storing data uploaded by a sensor node of the Internet of things;
s2, a data preprocessing module: preprocessing the data uploaded by the sensor to remove invalid data and abnormal data;
s3, a data mining analysis module: the core module is used for analyzing the data acquired from the preprocessing module;
s4, a decision instruction module: according to the data analysis result, intelligent control is carried out on the garden operation equipment;
s5, a user interface module: the module provides a user interface, which is convenient for a manager to monitor and manage the garden operation state in real time.
6. The garden job management system based on the internet of things according to claim 1, wherein the flow of the information acquisition and processing of the internet of things equipment is as follows:
(1) And (3) data acquisition: sensors on the device monitor the environment and device status, convert analog signals to digital signals through analog-to-digital converters, and the digital signals are received by the processor;
(2) And (3) data processing: the processor filters, cuts and processes the acquired data, converts the digital signals into data frames or data packets and transmits the data frames or data packets to the physical layer;
(3) And (3) data transmission: and transmitting the data packet to a cloud server through a wireless communication module.
7. A garden job management system based on internet of things according to claim 1, wherein the functions of the one or more sensor nodes corresponding to one or more garden job devices are implemented by:
(1) Configuring sensor node information;
(2) Establishing a corresponding relation of the equipment sensors;
(3) Monitoring data in real time and analyzing and processing the data;
(4) Device control and management;
the method for establishing the corresponding relation between the sensor and the garden operation equipment comprises the following steps:
(1) Based on physical location: the sensors are corresponding to the garden operation equipment according to the physical positions, so that the monitoring range of each sensor is ensured to be matched with the operation requirement of the equipment;
(2) Based on device type and attributes: establishing a corresponding relation between equipment and a sensor according to the type and the attribute of the garden operation equipment;
(3) Based on the operating mode and sampling frequency: when the association relation between the sensor and the garden working equipment is not clear, the corresponding garden working equipment is determined according to the characteristics of the working mode, the sampling frequency, the precision and the like of the sensor.
8. The garden job management system based on the internet of things according to claim 1, wherein the data storage and analysis processing system performs analysis processing on the uploaded data by adopting the following modes:
(1) And (3) data acquisition: uploading the data to a cloud end through an Internet of things node;
(2) And (3) cleaning data: processing the useless data through data cleaning, wherein the useless data comprise abnormal values, invalid values, repeated values and the like;
in the above steps, the data cleaning adopts the following steps:
(2.1), data preprocessing: preliminary processing is carried out on the original data;
(2.2), abnormal data detection: detecting abnormal data of the processed data, and finding out noise and outliers in the data; and the detected abnormal value is selected to be deleted, replaced or interpolated;
(2.3), data deduplication: performing deduplication processing on the repeated data, and guaranteeing the data uniqueness in the whole system;
(2.4), data accuracy verification: on one hand, repeated measurement values of the sensor are used, and on the other hand, a formula or a model is utilized to check the sensor data;
(3) And (3) data integration: integrating the acquired data into a data table, and normalizing, standardizing and normalizing the data to prepare for subsequent analysis;
(4) And (3) data statistical analysis: trend analysis, anomaly detection, association analysis and classification cluster analysis are carried out on the integrated data through a big data analysis technology;
(5) Machine learning model training and application: predicting the state and abnormal indexes of garden operation equipment, and predicting equipment faults in advance;
(6) Visualization of data: the statistical analysis results are visually displayed in the forms of icons, tables and the like, so that an administrator can conveniently know the state and the management condition of the garden operation equipment;
the mode of feeding back the decision result to the node of the internet of things can be realized by the following modes:
(1) Feedback via cloud platform: the data storage and analysis processing system feeds back an analysis result to the node of the Internet of things through the cloud platform and issues a corresponding instruction;
(2) Feedback through the local management platform: the management platform controls the node of the Internet of things, feeds the analyzed and processed data back to the management platform, generates corresponding management operation and sends the management operation to the node of the Internet of things.
9. The garden operation management system based on the internet of things according to claim 1, wherein the intelligent control method for the garden operation equipment is as follows:
(1) Controlling the working state of the garden working equipment: after the node of the Internet of things receives the feedback data, different garden operation requirements can be met by controlling the working state of the garden operation equipment;
(2) Parameter setting for controlling garden operation equipment: aiming at different garden operation equipment, different operation requirements are met by controlling equipment parameters.
10. The system of claim 1, wherein the sensor comprises:
(1) Temperature sensor: the temperature state monitoring device is used for monitoring the temperature state of the garden operation equipment in real time;
(2) Humidity sensor: the system is used for monitoring the humidity state of the garden operation equipment in real time;
(3) Illumination intensity sensor: the system is used for monitoring the illumination state of the garden operation equipment in real time;
(4) CO2 sensor: the system is used for monitoring the concentration of CO2 in the garden operation equipment in real time;
(5) Water quality sensor: the water quality monitoring device is used for monitoring the water quality in the garden operation equipment in real time.
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