Intelligent temperature control system for greenhouse

Abstract

The invention discloses an intelligent temperature control system for a greenhouse, and relates to the technical field of greenhouse temperature control, the intelligent temperature control system comprises a data acquisition module, a crop growth database module, a data analysis decision module, a remote monitoring alarm module, an intelligent control module and a user interaction interface module, all the modules are connected through electric signals. The temperature environment in the greenhouse is monitored in real time, accurate regulation and control are performed according to the growth requirements of crops and the current environmental conditions, the crops are ensured to be in the most suitable growth temperature range all the time, healthy growth and development of the crops are promoted, compared with a traditional manual regulation and control mode, temperature fluctuation can be more accurately controlled, and the crop yield is improved. The problems of crop growth resistance, increase of plant diseases and insect pests and the like caused by inappropriate temperature are avoided, in addition, the temperature set value can be automatically adjusted according to different growth stages and types of crops, the growth environment is further optimized, and the yield and quality of the crops are improved.

Description

Technical Field

[0001] The invention relates to the technical field of greenhouse temperature control, and in particular to an intelligent temperature control system for a greenhouse. Background Art

[0002] As an important agricultural production method, agricultural greenhouses have the characteristics of controllable facility environment, energy and water conservation, and high production efficiency. With the continuous development of agricultural technology, traditional agricultural production methods are gradually shifting towards modernization and intelligence. In greenhouse cultivation, temperature is one of the key factors affecting the growth of crops. Different crops have strict requirements on temperature at different growth stages. By controlling the temperature in the greenhouse, the most suitable growth environment can be provided for crops. This is an important means to improve crop yield and quality in the context of agricultural modernization.

[0003] For example, Chinese patent publication number: CN113687671A is a control system for intelligently adjusting the temperature of a greenhouse, which includes a controller, a top ventilation device, multiple side ventilation devices, multiple internal fans, a water curtain, and multiple negative pressure fans. The controller determines whether the current temperature detection value in the greenhouse is higher than a preset first temperature threshold. If so, one of the internal fans is controlled to be turned on; if the temperature detection value in the greenhouse has an upward trend, at least one of the remaining internal fans is controlled to be turned on.

[0004] In the prior art, the greenhouse temperature is controlled in combination with meteorological information. The factors affecting the temperature change in the greenhouse are monitored by temperature sensors and light sensors, and the temperature in the greenhouse is efficiently adjusted, which solves the problem of lag and low efficiency in controlling the greenhouse temperature by manual observation. However, different crops have different sensitivity and requirements for temperature at different growth stages, and it is difficult to adjust the temperature according to the needs of the crops, which makes it difficult to dynamically match the growth needs of crops in practical applications, thereby affecting the yield and quality of the crops. Therefore, how to dynamically adjust and optimize the temperature control requirements according to the crop planting data to meet the temperature requirements of the crops is a problem we need to solve. To this end, an intelligent temperature control system for greenhouses is proposed. Summary of the invention

[0005] The purpose of the present invention is to provide an intelligent temperature control system for a greenhouse to solve the problems raised in the above background technology.

[0006] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0007] An intelligent temperature control system for a greenhouse, the intelligent temperature control system comprising a data acquisition module, a crop growth database module, a data analysis and decision module, a remote monitoring and alarm module, an intelligent control module and a user interaction interface module, wherein electrical signals are connected between the modules;

[0008] The data acquisition module collects environmental data through various sensors deployed in the greenhouse, senses changes in ambient temperature, ensures the accuracy and real-time nature of the data, and provides a reliable basis for subsequent analysis and control;

[0009] The crop growth database module constructs a crop growth database, pre-stores planting data on the temperature, humidity, and light requirements of different crops at various growth stages, the data is derived from long-term agricultural scientific research practices, planting experience summaries, etc., and constructs a crop growth model to predict the suitable temperature range of crops at different stages, providing a basis for intelligent control;

[0010] The data analysis and decision module receives the environmental data acquired by the data acquisition module, compares and analyzes it with the crop growth model, calculates the environmental parameter deviation value, determines whether to adjust the temperature in the greenhouse, and determines the target value of the adjustment;

[0011] The remote monitoring alarm module remotely monitors the environmental data in the greenhouse, evaluates the degree of deviation of the overall environment in the greenhouse according to the degree of deviation of the environmental data in the greenhouse, and sends an alarm message to the grower so that timely measures can be taken for manual intervention;

[0012] The intelligent control module controls the temperature control equipment in the greenhouse according to the output of the remote monitoring alarm module, and dynamically adjusts the temperature in the greenhouse. The temperature control equipment includes ventilation fans, sunshade nets, and heating equipment to achieve precise temperature control and ensure that the crops are in the best growth environment.

[0013] The user interaction interface module, combined with the output of the intelligent control module, sends various control parameters in the greenhouse to the grower, displays real-time environmental data in the greenhouse, crop growth status and operating status of the temperature control equipment, allows users to manually adjust temperature control parameters, or view historical data and reports, thereby enhancing the flexibility of the system and user participation.

[0014] A further improvement of the technical solution of the present invention is that in the data acquisition module, the environmental data acquisition process includes:

[0015] Deploy various sensors in the greenhouse, including temperature sensors, humidity sensors, and light sensors. Plan the distribution of sensors according to the area and shape of the greenhouse to ensure that the sensors can fully cover the internal area of ​​the greenhouse and collect environmental data without omission. Use fixed brackets to install sensors at different heights and locations in the greenhouse to obtain more comprehensive environmental information.

[0016] Initialize and set up various sensors, including calibration, setting sampling frequency, and configuring communication parameters to ensure that the sensors can work normally and transmit data accurately. The sensors collect environmental data in the greenhouse in real time according to the preset sampling frequency, including temperature, humidity, and light intensity;

[0017] The sensor converts the collected raw data into digital signals through the internal analog-to-digital converter (ADC) and pre-processes the collected environmental data, including data smoothing, denoising, and filtering;

[0018] The sensor transmits the pre-processed environmental data to the data center of the intelligent temperature control system through the communication interface, and builds a data warehouse in the data center to store the pre-processed environmental data.

[0019] A further improvement of the technical solution of the present invention is that: in the crop growth database module, the construction process of the crop growth database includes:

[0020] Based on long-term agricultural scientific research practice, planting experience summary, agricultural expert consultation, agricultural literature and journals, etc., the data from different sources are uniformly formatted and standardized, integrating the temperature, humidity, and light demand data of different crops at various growth stages (sowing period, growth period, flowering period, fruiting period, etc.), as well as crop growth cycle, growth rate, and yield information;

[0021] Build a crop growth database, enter the integrated data into the database and store them according to crop types, growth stages, and environmental parameters to ensure the accuracy and completeness of the data, and verify and clean the data to remove outliers and duplicate data;

[0022] According to the characteristics and laws of crop growth, the crop growth model is constructed by combining the data in the crop growth database with the neural network model to analyze the relationship between crop growth and environmental parameters;

[0023] According to the current time, crop type and growth stage, the corresponding environmental parameter demand data is obtained from the crop growth database, and the input data is input into the trained crop growth model for predictive calculation. The suitable temperature range, humidity range, and light intensity environmental parameters of the crop in the current growth stage are output, and the prediction results are analyzed and interpreted to understand the growth status and needs of the crop under the current environmental conditions.

[0024] A further improvement of the technical solution of the present invention is that in the data analysis and decision module, the calculation process of the environmental parameter deviation value includes:

[0025] Extract the pre-processed environmental data of various environmental parameters (temperature, humidity, light intensity) from the data warehouse, and extract the optimal environmental parameter range corresponding to the current crop type and growth stage from the crop growth database according to the current time, crop type and growth stage, including the ideal value and acceptable range of temperature, humidity and light intensity;

[0026] Compare and analyze the extracted environmental data with the optimal environmental parameters in the crop growth model, calculate the environmental parameter deviation values, namely the temperature deviation value, humidity deviation value and light intensity deviation value, that is, the difference between the current value and the ideal value, analyze the size of the deviation value, and determine the degree of difference between the current environmental data and the ideal crop growth conditions;

[0027] According to the characteristics of crop types and growth stages, the deviation threshold of each environmental parameter is set, and the deviation value of each environmental parameter is compared with the environmental parameter deviation threshold to determine whether the temperature in the greenhouse needs to be adjusted. If adjustment is required, the target value to be adjusted is determined, that is, which environmental parameter value can meet the optimal growth conditions of the crop.

[0028] A further improvement of the technical solution of the present invention is that the calculation formula of the temperature deviation value is:

[0029]

[0030] Among them, T d is the temperature deviation value, T cu is the current temperature value, T id is the ideal temperature, T r is the acceptable temperature range, T d The value range is from 0 to 1, where 0 means the current temperature is exactly the same as the ideal temperature and 1 means the current temperature is outside the acceptable range;

[0031] The calculation formula of the humidity deviation value is:

[0032]

[0033] Among them, H d is the humidity deviation value, H cu is the current humidity value, H id is the ideal humidity value, H r is the acceptable range of humidity, H d The value range of is 0 to 1, where 0 means the current humidity is exactly the same as the ideal humidity and 1 means the current humidity is beyond the acceptable range;

[0034] The calculation formula of the light intensity deviation value is:

[0035]

[0036] Among them, L d is the light intensity deviation value, L cu is the current light intensity value, L id is the ideal light intensity value, L r is the acceptable range of light intensity, L d The value range is from 0 to 1, where 0 means that the current light intensity is exactly the same as the ideal light intensity, and 1 means that the current light intensity exceeds the acceptable range.

[0037] A further improvement of the technical solution of the present invention is that in the remote monitoring alarm module, the evaluation process of the overall environmental deviation degree in the greenhouse includes:

[0038] Monitor the environmental status in the greenhouse by analyzing the environmental data collected in real time by various types of sensors in the greenhouse (temperature sensor, humidity sensor, light sensor);

[0039] Combined with the data provided by the data analysis and decision-making module, the deviation values ​​of various environmental parameters are obtained, and the influence weights of temperature, humidity and light intensity are set according to the influence of different environmental parameters on crop growth;

[0040] Comprehensively analyze the deviation values ​​of various environmental parameters and the weight of their impact on crop growth, and calculate the environmental deviation evaluation coefficient based on the maximum acceptable deviation values ​​of temperature, humidity, and light intensity to evaluate the degree of deviation of the overall environment in the greenhouse;

[0041] According to the crop type, growth stage and actual needs of the grower, the dynamic alarm threshold of the environmental deviation evaluation coefficient is set. According to the environmental deviation evaluation coefficient, the deviation degree of the environmental data in the greenhouse is analyzed to see whether it exceeds the preset alarm threshold. When the environmental deviation evaluation coefficient exceeds the set alarm threshold, the alarm mechanism is triggered.

[0042] Once the alarm mechanism is triggered, the remote monitoring module automatically generates an alarm message, which includes the greenhouse number, the deviation value of each environmental parameter, the environmental deviation evaluation coefficient, and the recommended intervention measures. The generated alarm information is sent to the grower via SMS, email, and APP push to ensure that the grower can receive the alarm information in time and understand the environmental conditions in the greenhouse.

[0043] A further improvement of the technical solution of the present invention is that the dynamic alarm threshold specifically includes:

[0044] The alarm threshold is based on the crop growth stage. The crop growth stage includes the sowing period, the growing period, the flowering period, and the fruiting period. The alarm is triggered when the environmental deviation evaluation coefficient exceeds 0.3 during the sowing period, the alarm is triggered when the environmental deviation evaluation coefficient exceeds 0.4 during the growing period, and the alarm is triggered when the environmental deviation evaluation coefficient exceeds 0.2 during the flowering period, because the flowering period is very sensitive to environmental changes. The alarm is triggered when the environmental deviation evaluation coefficient exceeds 0.35 during the fruiting period;

[0045] Alarm thresholds based on crop types: for heat-resistant crops, an alarm is triggered when the environmental deviation evaluation coefficient exceeds 0.4; for cold-resistant crops, an alarm is triggered when the environmental deviation evaluation coefficient exceeds 0.25; for crops that are sensitive to humidity, the humidity deviation value has a higher weight, and an alarm is triggered when the environmental deviation evaluation coefficient exceeds 0.3;

[0046] Alarm thresholds based on grower needs: for high-value crops, an alarm is triggered when the environmental deviation evaluation coefficient exceeds 0.2 to ensure optimal growing conditions for crops; for large-scale cultivated crops, an alarm is triggered when the environmental deviation evaluation coefficient exceeds 0.45 to reduce false alarms and unnecessary interventions.

[0047] A further improvement of the technical solution of the present invention is that the calculation formula of the environmental deviation evaluation coefficient is:

[0048]

[0049] Among them, E c is the environmental deviation evaluation coefficient, T d is the temperature deviation value, which indicates the difference between the current temperature and the ideal temperature. d is the humidity deviation value, which indicates the difference between the current humidity and the ideal humidity, L d is the light intensity deviation value, which indicates the difference between the current light intensity and the ideal light intensity, w T 、w H 、w L are the influence weights of temperature, humidity, and light intensity, respectively, reflecting the importance of each parameter on crop growth. B is the adjustment parameter, which is a constant used to adjust the sensitivity of the exponential function. max , H max , L max They are the maximum acceptable deviation values ​​of temperature, humidity and light intensity respectively. The value range of Ec is limited to between 0 and 1, where 0 means that the environmental parameters are completely consistent with the ideal values, and 1 means that the environmental parameters deviate greatly.

[0050] A further improvement of the technical solution of the present invention is that: in the intelligent control module, the process of dynamically adjusting the temperature in the greenhouse includes:

[0051] The intelligent control module receives data from each sensor through the input interface and receives signals sent by the remote monitoring alarm module;

[0052] Analyze the temperature data, environmental deviation evaluation coefficient and alarm status in the signal to determine whether the current temperature is within the appropriate range. If it is within the appropriate range, further analyze the temperature change trend to predict whether it is about to exceed the appropriate range and make preparations for adjustment in advance.

[0053] If the current temperature has exceeded the suitable range, determine whether it is higher or lower than the optimal temperature range, and the extent of the excess. Combined with the temperature change trend, comprehensively evaluate the adjustment measures that need to be taken to return the temperature to the suitable range and ensure that the crops are in the best growth environment;

[0054] If the current temperature is higher than the suitable temperature range for the current growth stage of the crop, and the temperature is still rising according to the trend of change, the intelligent control module generates corresponding control decision instructions, and gives priority to increasing the speed of the ventilation fan to speed up air circulation and enhance the heat dissipation effect. If the temperature drop is not ideal after ventilation adjustment, the opening and closing degree of the sunshade net is further adjusted to increase the sunshade area, reduce the heat brought by direct sunlight, and reduce the power of the heating equipment or turn off the heating equipment, so as to quickly reduce the temperature in the greenhouse through the synergy of multiple devices;

[0055] If the current temperature is lower than the suitable range and the temperature is decreasing, the intelligent control module decides to start the heating equipment (the power level of the heating equipment is determined according to the difference between the temperature and the suitable range. The larger the difference, the higher the starting power). At the same time, the speed of the ventilation fan is reduced to reduce heat loss, and part of the sunshade net is retracted to increase sunlight for heat supplement, so as to raise the temperature in the greenhouse to the suitable range as soon as possible.

[0056] If the temperature is currently in a suitable range but is about to exceed it, specifically rising slowly towards the upper limit or falling slowly towards the lower limit, the intelligent control module will make fine-tuning decisions in advance, fine-tuning the speed of the ventilation fan or the degree of opening and closing of the sunshade net to prevent the temperature from exceeding the optimal range in advance, maintain relative temperature stability, and ensure that the crops are always in a good growth temperature environment.

[0057] Due to the adoption of the above technical solution, the present invention has the following technical advances compared with the prior art:

[0058] 1. The present invention provides an intelligent temperature control system for a greenhouse, which monitors the temperature environment in the greenhouse in real time and performs precise regulation according to the growth requirements of the crops and the current environmental conditions to ensure that the crops are always within the most suitable growth temperature range, thereby promoting the healthy growth and development of the crops. Compared with the traditional manual regulation method, it can more accurately control temperature fluctuations, avoid problems such as crop growth stagnation and increased pests and diseases caused by unsuitable temperature, and in addition, it can automatically adjust the temperature setting value according to the different growth stages and types of the crops, further optimize the growth environment, and improve the yield and quality of the crops.

[0059] 2. The present invention provides an intelligent temperature control system for greenhouses. By real-time monitoring and analysis of temperature data in the greenhouse, the operation of temperature control equipment can be accurately controlled, thereby avoiding unnecessary energy waste. It can also detect abnormal changes in the temperature environment in the greenhouse in advance and send out early warning signals, so that growers can promptly discover and deal with potential problems, avoiding crop losses due to abnormal temperatures, ensuring the stable operation of the system, and improving the production efficiency of the greenhouse. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0061] Figure 1 It is a module diagram of the present invention;

[0062] Figure 2 is a flow chart for calculating the environmental parameter deviation value of the present invention;

[0063] Figure 3 This is a flow chart for evaluating the overall environmental deviation degree in the greenhouse of the present invention. DETAILED DESCRIPTION

[0064] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0065] Embodiment 1, as Figure 1 , Figure 2As shown, the present invention provides an intelligent temperature control system for greenhouses, the intelligent temperature control system includes a data acquisition module, a crop growth database module, a data analysis and decision module, a remote monitoring and alarm module, an intelligent control module and a user interaction interface module, wherein the modules are connected by electrical signals;

[0066] The data acquisition module collects environmental data through various sensors deployed in the greenhouse, senses changes in ambient temperature, ensures the accuracy and real-time nature of the data, and provides a reliable basis for subsequent analysis and control. Various sensors are deployed in the greenhouse, including temperature sensors, humidity sensors, and light sensors. The distribution of sensors is planned according to the area and shape of the greenhouse to ensure that the sensors can fully cover the internal area of ​​the greenhouse and collect environmental data without omission. Sensors are installed at different heights and positions in the greenhouse using fixed brackets to obtain more comprehensive environmental information. Initialization settings are performed for various sensors, including calibration, setting sampling frequency, and configuring communication parameters to ensure that the sensors can work normally and transmit data accurately. The sensors are set according to the preset sampling frequency. The environmental data in the greenhouse is collected in real time at a high rate, wherein the environmental data include temperature, humidity, and light intensity. The sensor converts the collected raw data into digital signals through the internal analog-to-digital converter (ADC), and pre-processes the collected environmental data, including data smoothing, denoising, and filtering. The collected environmental data is smoothed to reduce data fluctuations caused by sensor noise or environmental interference, and denoising is performed to remove abnormal values ​​or noise points in the data to improve data accuracy. A filtering algorithm is applied to further smooth the data to improve data reliability. The sensor transmits the pre-processed environmental data to the data center of the intelligent temperature control system through a communication interface, and a data warehouse is built in the data center to store the pre-processed environmental data;

[0067] The crop growth database module builds a crop growth database and pre-stores planting data on the temperature, humidity, and light requirements of different crops at various growth stages. The data comes from long-term agricultural scientific research practices, planting experience summaries, etc., and builds a crop growth model to predict the suitable temperature range of crops at different stages to provide a basis for intelligent control. Based on long-term agricultural scientific research practices, planting experience summaries, agricultural expert consultations, agricultural literature and journals, etc., data from different sources are uniformly formatted and standardized, and the temperature, humidity, and light requirements of different crops at various growth stages (sowing period, growth period, flowering period, fruiting period, etc.) are integrated, as well as crop growth cycles, growth rates, and yield information to build a crop growth database. The integrated data is entered into the database and stored in categories according to crop types, growth stages, and environmental parameters to ensure the accuracy and completeness of the data, and the data is censored. Verify and clean, remove outliers and duplicate data, build a crop growth model based on the characteristics and laws of crop growth, use the data in the crop growth database combined with the neural network model, analyze the relationship between crop growth and environmental parameters, and train and optimize the model. By adjusting the parameters and structure of the model, improve the prediction accuracy and generalization ability of the model. Use an independent test data set to verify and evaluate the trained model. According to the verification results, adjust and improve the model. According to the current time, crop type and growth stage, obtain the corresponding environmental parameter demand data from the crop growth database, input the input data into the trained crop growth model, perform prediction calculations, and output the suitable temperature range, humidity range, and light intensity environmental parameters of the crop in the current growth stage. Analyze and interpret the prediction results to understand the growth status and needs of crops under the current environmental conditions;

[0068] The data analysis and decision module receives the environmental data obtained by the data acquisition module, compares and analyzes it with the crop growth model, calculates the environmental parameter deviation value, clarifies whether to adjust the temperature in the greenhouse, and determines the target value of the adjustment. The pre-processed environmental data of each environmental parameter (temperature, humidity, light intensity) is extracted from the data warehouse, and according to the current time, crop type and growth stage, the optimal environmental parameter range corresponding to the current crop type and growth stage is extracted from the crop growth database, including the ideal value and acceptable range of temperature, humidity and light intensity. The extracted environmental data are compared and analyzed with the optimal environmental parameters in the crop growth model, and the environmental parameter deviation values ​​are calculated, which are the temperature deviation value, humidity deviation value and light intensity deviation value, that is, the difference between the current value and the ideal value. The size of the deviation value is analyzed to determine the degree of difference between the current environmental data and the ideal growth conditions of the crop. According to the characteristics of the crop type and growth stage, the deviation threshold of each environmental parameter is set, and the deviation value of each environmental parameter is compared with the environmental parameter deviation threshold to determine whether the temperature in the greenhouse needs to be adjusted. If adjustment is required, the target value to be adjusted is determined, that is, which environmental parameter value can meet the optimal growth conditions of the crop.

[0069] Furthermore, the temperature deviation value is calculated as follows:

[0070]

[0071] Among them, T d is the temperature deviation value, T cu is the current temperature value, T id is the ideal temperature, T r is the acceptable temperature range, T d The value range is from 0 to 1, where 0 means the current temperature is exactly the same as the ideal temperature and 1 means the current temperature is outside the acceptable range;

[0072] The calculation formula for humidity deviation value is:

[0073]

[0074] Among them, H d is the humidity deviation value, H cu is the current humidity value, H id is the ideal humidity value, H r is the acceptable range of humidity, H d The value range of is 0 to 1, where 0 means the current humidity is exactly the same as the ideal humidity and 1 means the current humidity is beyond the acceptable range;

[0075] The calculation formula of light intensity deviation value is:

[0076]

[0077] Among them, L d is the light intensity deviation value, L cu is the current light intensity value, L id is the ideal light intensity value, L r is the acceptable range of light intensity, L d The value range of is 0 to 1, where 0 means that the current light intensity is exactly the same as the ideal light intensity, and 1 means that the current light intensity exceeds the acceptable range;

[0078] Remote monitoring and alarm module: remotely monitors the environmental data in the greenhouse, evaluates the deviation of the overall environment in the greenhouse according to the deviation of the environmental data in the greenhouse, and sends alarm information to the grower so that timely measures can be taken for manual intervention;

[0079] The intelligent control module controls the temperature control equipment in the greenhouse according to the output of the remote monitoring alarm module, and dynamically adjusts the temperature in the greenhouse. The temperature control equipment includes ventilation fans, sunshade nets, and heating equipment to achieve precise temperature control and ensure that crops are in the best growth environment;

[0080] The user interaction interface module, combined with the output of the intelligent control module, sends various control parameters in the greenhouse to the grower, displays real-time environmental data in the greenhouse, crop growth status and the operating status of the temperature control equipment, and allows users to manually adjust temperature control parameters or view historical data and reports, thereby enhancing the flexibility of the system and user participation.

[0081] Embodiment 2, as Figure 3 As shown, based on Example 1, the present invention provides a technical solution: Preferably, in the remote monitoring alarm module, the evaluation process of the overall environmental deviation degree in the greenhouse includes:

[0082] By analyzing the environmental data collected in real time by various types of sensors (temperature sensor, humidity sensor, light sensor) in the greenhouse, monitoring the environmental status in the greenhouse, combining the data provided by the data analysis decision module, obtaining the deviation value of each environmental parameter, and setting the influence weight of temperature, humidity and light intensity according to the influence degree of different environmental parameters on crop growth, comprehensively analyzing the deviation value of each environmental parameter and the influence weight on crop growth, and combining the maximum acceptable deviation value of temperature, humidity and light intensity, calculating the environmental deviation evaluation coefficient, evaluating the deviation degree of the overall environment in the greenhouse, setting the dynamic alarm threshold of the environmental deviation evaluation coefficient according to the crop type, growth stage and the actual needs of the grower, analyzing whether the deviation degree of the environmental data in the greenhouse exceeds the preset alarm threshold according to the environmental deviation evaluation coefficient, and triggering the alarm mechanism when the environmental deviation evaluation coefficient exceeds the set alarm threshold. Once the alarm mechanism is triggered, the remote monitoring module automatically generates an alarm message, which includes the greenhouse number, the deviation value of each environmental parameter, the environmental deviation evaluation coefficient, and the recommended intervention measures, and sends the generated alarm message to the grower through SMS, email, and APP push to ensure that the grower can receive the alarm message in time and understand the environmental conditions in the greenhouse;

[0083] Furthermore, the dynamic alarm threshold specifically includes:

[0084] The alarm thresholds are based on the crop growth stages, which include the sowing period, the growing period, the flowering period, and the fruiting period. The alarm is triggered when the environmental deviation evaluation coefficient exceeds 0.3 during the sowing period, when it exceeds 0.4 during the growing period, and when it exceeds 0.2 during the flowering period, because the flowering period is very sensitive to environmental changes. The alarm is triggered when the environmental deviation evaluation coefficient exceeds 0.35 during the fruiting period. The alarm thresholds are based on the crop types. For heat-resistant crops, the alarm is triggered when the environmental deviation evaluation coefficient exceeds 0.4. For cold-resistant crops, the alarm is triggered when the environmental deviation evaluation coefficient exceeds 0.25. For crops that are sensitive to humidity, the weight of the humidity deviation value is higher, and the alarm is triggered when the environmental deviation evaluation coefficient exceeds 0.3. The alarm thresholds are based on the needs of growers. For high-value crops, the alarm is triggered when the environmental deviation evaluation coefficient exceeds 0.2 to ensure the best growth conditions for crops. For large-scale crops, the alarm is triggered when the environmental deviation evaluation coefficient exceeds 0.45 to reduce false alarms and unnecessary interventions.

[0085] Furthermore, the calculation formula of the environmental deviation evaluation coefficient is:

[0086]

[0087] Among them, E c is the environmental deviation evaluation coefficient, T dis the temperature deviation value, which indicates the difference between the current temperature and the ideal temperature. d is the humidity deviation value, which indicates the difference between the current humidity and the ideal humidity, L d is the light intensity deviation value, which indicates the difference between the current light intensity and the ideal light intensity, w T 、w H 、w L are the influence weights of temperature, humidity, and light intensity, respectively, reflecting the importance of each parameter on crop growth. B is the adjustment parameter, which is a constant used to adjust the sensitivity of the exponential function. max , H max , L max are the maximum acceptable deviations of temperature, humidity and light intensity, E c The value range of E is limited to between 0 and 1, where 0 means that the environmental parameters are completely consistent with the ideal value, and 1 means that the environmental parameters have a large deviation. When the deviation value of the environmental parameters increases, E c As the value increases, it means that the environmental conditions deviate from the ideal state. When the deviation value of the environmental parameters decreases, E c The value decreases, indicating that the environmental conditions are closer to the ideal state;

[0088] In the intelligent control module, the process of dynamically adjusting the temperature in the greenhouse includes:

[0089] The intelligent control module receives data from each sensor through the input interface, and receives the signal sent by the remote monitoring alarm module, analyzes the temperature data, environmental deviation evaluation coefficient and alarm status in the signal, and determines whether the current temperature is within the appropriate range. If it is within the appropriate range, further analyze the temperature change trend, predict whether it is about to exceed the appropriate range, and make adjustment preparations in advance. If the current temperature has exceeded the appropriate range, determine whether it is higher or lower than the optimal temperature range, and the extent of the excess. At the same time, combined with the temperature change trend, comprehensively evaluate the adjustment measures to be taken to return the temperature to the appropriate range and ensure that the crops are in the best growth environment. If the current temperature is higher than the appropriate temperature range for the current growth stage of the crop, and the temperature is still rising according to the change trend, the intelligent control module generates corresponding control decision instructions, and gives priority to increasing the speed of the ventilation fan to speed up air circulation and enhance the heat dissipation effect. If the temperature drop is not ideal after ventilation adjustment, further adjust the shade The opening and closing degree of the sunshade net increases the shading area, reduces the heat brought by direct sunlight, and reduces the power of the heating equipment or turns off the heating equipment. The temperature in the greenhouse can be quickly lowered through the synergy of multiple devices. If the current temperature is lower than the suitable range and the temperature is on a downward trend, the intelligent control module decides to start the heating equipment (the power level of the heating equipment is determined according to the difference between the temperature and the suitable range. The larger the difference, the higher the starting power). At the same time, the speed of the ventilation fan is reduced to reduce heat loss, and part of the sunshade net is retracted to increase sunlight for heat supplement, so as to raise the temperature in the greenhouse to the suitable range as soon as possible. If the temperature is currently in the suitable range, but there is a trend of exceeding it, specifically a slow rise approaching the upper limit or a slow fall approaching the lower limit, the intelligent control module makes fine-tuning decisions in advance, fine-tunes the speed of the ventilation fan or the opening and closing degree of the sunshade net, prevents the temperature from exceeding the optimal range in advance, maintains the temperature relatively stable, and ensures that the crops are always in a good growth temperature environment.

[0090] The above are only specific implementations of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. An intelligent temperature control system for a greenhouse, characterized in that: The intelligent temperature control system includes a data acquisition module, a crop growth database module, a data analysis and decision module, a remote monitoring and alarm module, an intelligent control module and a user interaction interface module, wherein the modules are connected by electrical signals; The data acquisition module collects environmental data through various sensors deployed in the greenhouse; The crop growth database module constructs a crop growth database, pre-stores the planting data required for different crops at various growth stages, and constructs a crop growth model to predict the suitable temperature range for crops at different stages; The data analysis and decision module receives environmental data, compares and analyzes it with the crop growth model, calculates the environmental parameter deviation value, determines whether to adjust the temperature in the greenhouse, and determines the target value for adjustment; The remote monitoring alarm module remotely monitors the environmental data in the greenhouse, evaluates the degree of deviation of the overall environment in the greenhouse, and sends alarm information to the grower; The intelligent control module controls the temperature control equipment in the greenhouse according to the output of the remote monitoring alarm module, and dynamically adjusts the temperature in the greenhouse; The user interaction interface module displays real-time environmental data in the greenhouse, crop growth status, and operating status of the temperature control equipment, allowing the user to manually adjust the temperature control parameters.

2. The intelligent temperature control system for greenhouse according to claim 1, characterized in that: In the data collection module, the process of collecting environmental data includes: Deploy various sensors in the greenhouse, including temperature sensors, humidity sensors, and light sensors. Plan the distribution of sensors according to the area and shape of the greenhouse, and use fixed brackets to install the sensors at different heights and locations in the greenhouse; Initialize the settings of various sensors, including calibration, setting sampling frequency, and configuring communication parameters. The sensors collect environmental data in the greenhouse in real time according to the preset sampling frequency. The environmental data includes temperature, humidity, and light intensity. The sensor converts the collected raw data into digital signals through the internal analog-to-digital converter and pre-processes the collected environmental data, including data smoothing, denoising, and filtering; The sensor transmits the pre-processed environmental data to the data center of the intelligent temperature control system through the communication interface, and builds a data warehouse in the data center to store the pre-processed environmental data.

3. The intelligent temperature control system for greenhouse according to claim 2, characterized in that: In the crop growth database module, the construction process of the crop growth database includes: Based on agricultural research practices, planting experience summaries, and agricultural literature, data from different sources are uniformly formatted and standardized, integrating data on the temperature, humidity, and light requirements of different crops at various growth stages, as well as crop growth cycles, growth rates, and yield information; Build a crop growth database, enter the integrated data into the database for classification and storage according to crop type, growth stage, and environmental parameters, and verify and clean the data; According to the characteristics and laws of crop growth, the crop growth model is constructed by combining the data in the crop growth database with the neural network model to analyze the relationship between crop growth and environmental parameters; According to the current time, crop type and growth stage, the corresponding environmental parameter demand data is obtained from the crop growth database, and the input data is input into the trained crop growth model for predictive calculation to output the suitable temperature range, humidity range and light intensity environmental parameters of the crop in the current growth stage.

4. The intelligent temperature control system for greenhouse according to claim 3, characterized in that: In the data analysis and decision module, the calculation process of the environmental parameter deviation value includes: Extract the pre-processed environmental data of each environmental parameter from the data warehouse, and extract the optimal environmental parameter range corresponding to the current crop type and growth stage from the crop growth database according to the current time, crop type and growth stage, including the ideal value and acceptable range of temperature, humidity and light intensity; Compare and analyze the extracted environmental data with the optimal environmental parameters in the crop growth model, calculate the environmental parameter deviation values, namely, temperature deviation value, humidity deviation value, and light intensity deviation value, analyze the size of the deviation value, and determine the degree of difference between the current environmental data and the ideal crop growth conditions; According to the characteristics of crop types and growth stages, the deviation threshold of each environmental parameter is set, and the deviation value of each environmental parameter is compared with the environmental parameter deviation threshold to determine whether the temperature in the greenhouse needs to be adjusted. If adjustment is required, the target value to be adjusted is determined.

5. The intelligent temperature control system for greenhouse according to claim 4, characterized in that: The calculation formula of the temperature deviation value is: Among them, T d is the temperature deviation value, T cu is the current temperature value, T id is the ideal temperature, T r is the acceptable temperature range, T d The value range is from 0 to 1, where 0 means the current temperature is exactly the same as the ideal temperature and 1 means the current temperature is outside the acceptable range; The calculation formula of the humidity deviation value is: Among them, H d is the humidity deviation value, H cu is the current humidity value, H id is the ideal humidity value, H r is the acceptable range of humidity, H d The value range of is 0 to 1, where 0 means the current humidity is exactly the same as the ideal humidity and 1 means the current humidity is beyond the acceptable range; The calculation formula of the light intensity deviation value is: Among them, L d is the light intensity deviation value, L cu is the current light intensity value, L id is the ideal light intensity value, L r is the acceptable range of light intensity, L d The value range is from 0 to 1, where 0 means that the current light intensity is exactly the same as the ideal light intensity, and 1 means that the current light intensity exceeds the acceptable range.

6. The intelligent temperature control system for greenhouse according to claim 5, characterized in that: In the remote monitoring alarm module, the evaluation process of the overall environmental deviation degree in the greenhouse includes: Monitor the environmental status in the greenhouse by analyzing the environmental data collected in real time by various types of sensors in the greenhouse; Combined with the data provided by the data analysis and decision-making module, the deviation values ​​of various environmental parameters are obtained, and the influence weights of temperature, humidity and light intensity are set according to the influence of different environmental parameters on crop growth; Comprehensively analyze the deviation values ​​of various environmental parameters and the weight of their impact on crop growth, and calculate the environmental deviation evaluation coefficient based on the maximum acceptable deviation values ​​of temperature, humidity, and light intensity to evaluate the degree of deviation of the overall environment in the greenhouse; According to the crop type, growth stage and actual needs of the grower, the dynamic alarm threshold of the environmental deviation evaluation coefficient is set. According to the environmental deviation evaluation coefficient, the deviation degree of the environmental data in the greenhouse is analyzed to see whether it exceeds the preset alarm threshold. When the environmental deviation evaluation coefficient exceeds the set alarm threshold, the alarm mechanism is triggered. Once the alarm mechanism is triggered, the remote monitoring module automatically generates alarm information, which includes the greenhouse number, the deviation value of each environmental parameter, the environmental deviation evaluation coefficient, and the recommended intervention measures. The generated alarm information will be sent to the grower via SMS, email, and APP push.

7. The intelligent temperature control system for greenhouse according to claim 6, characterized in that: The dynamic alarm threshold specifically includes: The alarm threshold is based on the crop growth stage, which includes the sowing period, the growing period, the flowering period, and the fruiting period. The alarm is triggered when the environmental deviation evaluation coefficient exceeds 0.3 during the sowing period, the alarm is triggered when the environmental deviation evaluation coefficient exceeds 0.4 during the growing period, the alarm is triggered when the environmental deviation evaluation coefficient exceeds 0.2 during the flowering period, and the alarm is triggered when the environmental deviation evaluation coefficient exceeds 0.35 during the fruiting period; Alarm thresholds based on crop types: for heat-resistant crops, an alarm is triggered when the environmental deviation evaluation coefficient exceeds 0.4; for cold-resistant crops, an alarm is triggered when the environmental deviation evaluation coefficient exceeds 0.25; for moisture-sensitive crops, an alarm is triggered when the environmental deviation evaluation coefficient exceeds 0.3; The alarm threshold is based on the needs of growers. For high-value crops, the alarm is triggered when the environmental deviation evaluation coefficient exceeds 0.

2. For large-scale cultivated crops, the alarm is triggered when the environmental deviation evaluation coefficient exceeds 0.

45.

8. The intelligent temperature control system for greenhouse according to claim 7, characterized in that: The calculation formula of the environmental deviation evaluation coefficient is: Among them, E c is the environmental deviation evaluation coefficient, T d is the temperature deviation value, H d is the humidity deviation value, L d is the light intensity deviation value, w T 、w H 、w L are the influence weights of temperature, humidity, and light intensity, respectively. B is the adjustment parameter, which is a constant used to adjust the sensitivity of the exponential function. max , H max , L max are the maximum acceptable deviations of temperature, humidity and light intensity, E c The value range is limited to between 0 and 1.

9. The intelligent temperature control system for greenhouse according to claim 8, characterized in that: In the intelligent control module, the process of dynamically adjusting the temperature in the greenhouse includes: The intelligent control module receives data from each sensor through the input interface and receives signals sent by the remote monitoring alarm module; Analyze the temperature data, environmental deviation evaluation coefficient and alarm status in the signal to determine whether the current temperature is within the appropriate range. If it is within the appropriate range, further analyze the temperature change trend to predict whether it is about to exceed the appropriate range. If the current temperature has exceeded the suitable range, determine whether it is higher or lower than the optimal temperature range, and the extent of the excess. Combined with the temperature change trend, comprehensively evaluate the adjustment measures that need to be taken to return the temperature to the suitable range; If the current temperature is higher than the suitable temperature range for the current growth stage of the crop, and the temperature is continuously rising according to the change trend, the intelligent control module generates corresponding control decision instructions, and gives priority to increasing the speed of the ventilation fan to speed up air circulation. If the temperature drop is not ideal after ventilation adjustment, the opening and closing degree of the sunshade net is further adjusted to increase the sunshade area, and the power of the heating equipment is reduced or the heating equipment is turned off; If the current temperature is lower than the appropriate range and the temperature is on a downward trend, the intelligent control module decides to start the heating equipment, reduce the speed of the ventilation fan, and retract some of the sunshade nets to increase sunlight for heat supplement; If the temperature is currently in a suitable range but is about to exceed it, specifically by slowly rising to an upper limit or slowly falling to a lower limit, the intelligent control module will make fine-tuning decisions in advance to fine-tune the speed of the ventilation fan or the degree of opening and closing of the sunshade net to maintain relative temperature stability.

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