CN110050673A - A kind of intelligent irrigation management system - Google Patents
A kind of intelligent irrigation management system Download PDFInfo
- Publication number
- CN110050673A CN110050673A CN201910363189.3A CN201910363189A CN110050673A CN 110050673 A CN110050673 A CN 110050673A CN 201910363189 A CN201910363189 A CN 201910363189A CN 110050673 A CN110050673 A CN 110050673A
- Authority
- CN
- China
- Prior art keywords
- irrigation
- soil
- water
- platform
- intelligent
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000003973 irrigation Methods 0.000 title claims abstract description 123
- 230000002262 irrigation Effects 0.000 title claims abstract description 122
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims abstract description 89
- 239000002689 soil Substances 0.000 claims abstract description 76
- 239000003621 irrigation water Substances 0.000 claims abstract description 39
- 230000005540 biological transmission Effects 0.000 claims abstract description 32
- QVFWZNCVPCJQOP-UHFFFAOYSA-N chloralodol Chemical compound CC(O)(C)CC(C)OC(O)C(Cl)(Cl)Cl QVFWZNCVPCJQOP-UHFFFAOYSA-N 0.000 claims abstract description 24
- 230000008447 perception Effects 0.000 claims abstract description 22
- 238000004364 calculation method Methods 0.000 claims description 16
- 238000005516 engineering process Methods 0.000 claims description 7
- 239000003673 groundwater Substances 0.000 claims description 7
- 230000008859 change Effects 0.000 claims description 4
- 238000005259 measurement Methods 0.000 claims description 4
- 238000011160 research Methods 0.000 claims description 3
- 238000000034 method Methods 0.000 description 11
- WHXSMMKQMYFTQS-UHFFFAOYSA-N Lithium Chemical compound [Li] WHXSMMKQMYFTQS-UHFFFAOYSA-N 0.000 description 8
- 238000004891 communication Methods 0.000 description 8
- 229910052744 lithium Inorganic materials 0.000 description 8
- 238000010586 diagram Methods 0.000 description 7
- 238000004146 energy storage Methods 0.000 description 5
- 238000012544 monitoring process Methods 0.000 description 5
- 230000006870 function Effects 0.000 description 4
- 230000008569 process Effects 0.000 description 4
- 239000003990 capacitor Substances 0.000 description 3
- 230000007613 environmental effect Effects 0.000 description 3
- 239000002699 waste material Substances 0.000 description 3
- 238000004590 computer program Methods 0.000 description 2
- 238000012937 correction Methods 0.000 description 2
- 230000004927 fusion Effects 0.000 description 2
- 230000003993 interaction Effects 0.000 description 2
- 230000000007 visual effect Effects 0.000 description 2
- 230000001154 acute effect Effects 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000032823 cell division Effects 0.000 description 1
- 239000011248 coating agent Substances 0.000 description 1
- 238000000576 coating method Methods 0.000 description 1
- 238000005260 corrosion Methods 0.000 description 1
- 238000013480 data collection Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000005265 energy consumption Methods 0.000 description 1
- 238000003384 imaging method Methods 0.000 description 1
- 229910052751 metal Inorganic materials 0.000 description 1
- 239000002184 metal Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000001556 precipitation Methods 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 230000005855 radiation Effects 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
- 230000009897 systematic effect Effects 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
Classifications
-
- A—HUMAN NECESSITIES
- A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
- A01G—HORTICULTURE; CULTIVATION OF VEGETABLES, FLOWERS, RICE, FRUIT, VINES, HOPS OR SEAWEED; FORESTRY; WATERING
- A01G25/00—Watering gardens, fields, sports grounds or the like
- A01G25/16—Control of watering
- A01G25/167—Control by humidity of the soil itself or of devices simulating soil or of the atmosphere; Soil humidity sensors
Landscapes
- Life Sciences & Earth Sciences (AREA)
- Soil Sciences (AREA)
- Engineering & Computer Science (AREA)
- Water Supply & Treatment (AREA)
- Environmental Sciences (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
本发明提供了一种智能灌溉管理系统，包括应用管理平台、云数据中心、无线传输平台和智能感知平台；所述应用管理平台包括智能终端和灌溉管理软件；所述智能感知平台包括数据采集控制器、LoRa传输模块、土壤墒情传感器、土壤温度传感器、水位传感器、气象环境传感器、水泵和电磁阀；所述云数据中心包括云服务器，所述云数据中心通过无线传输平台接收所述智能感知平台采集到的信息，根据采集到的信息和预设的灌溉用水需求模型生成作物需水预报和灌溉预报，并传输给灌溉管理软件，由灌溉管理软件生成相应的灌溉策略。本发明能够避免现有技术中的问题，可根据农作物对浇灌的不同要求设定不同的浇灌策略，实现个性化浇灌。
The invention provides an intelligent irrigation management system, including an application management platform, a cloud data center, a wireless transmission platform and an intelligent perception platform; the application management platform includes an intelligent terminal and irrigation management software; the intelligent perception platform includes a data acquisition control platform device, LoRa transmission module, soil moisture sensor, soil temperature sensor, water level sensor, meteorological environment sensor, water pump and solenoid valve; the cloud data center includes a cloud server, and the cloud data center receives the intelligent perception platform through a wireless transmission platform The collected information generates crop water demand forecast and irrigation forecast according to the collected information and the preset irrigation water demand model, and transmits it to the irrigation management software, and the irrigation management software generates the corresponding irrigation strategy. The invention can avoid the problems in the prior art, and can set different irrigation strategies according to the different requirements of crops for irrigation, so as to realize individualized irrigation.
Description
技术领域technical field
本发明涉及农业灌溉领域，尤其是一种基于采集到的土壤信息、气象信息，通过作物灌溉用水需求模型计算后，能够反馈调节用水信息进行灌溉的智能灌溉管理系统。The invention relates to the field of agricultural irrigation, in particular to an intelligent irrigation management system capable of feeding back and adjusting water information for irrigation based on collected soil information and meteorological information and after calculating through a crop irrigation water demand model.
背景技术Background technique
在我国农业用水约占用水总量的63％，传统农业灌溉模式水资源浪费严重，使得我国农业用水的有效利用率仅为45％左右。我国农业领域由于水资源利用率低以及耕地管理效率低等问题，制约了农业的发展。在灌溉期浇水全凭农民的经验和感觉，造成水资源的严重浪费，也使农作物不能得到最佳的生长环境，影响了农作物的产量和质量。依靠人工进行农业管理，不仅工作效率低、工作量大，而且不能长时间有效的进行作物需水情况监测，不利于灌溉的科学管理和先进灌溉技术的推广。In my country, agricultural water accounts for about 63% of the total water, and the traditional agricultural irrigation mode wastes water resources seriously, so that the effective utilization rate of agricultural water in my country is only about 45%. In my country's agricultural field, problems such as low utilization of water resources and low efficiency of cultivated land management restrict the development of agriculture. Watering during the irrigation period is entirely based on the experience and feeling of farmers, resulting in a serious waste of water resources, and also preventing crops from getting the best growth environment, affecting the yield and quality of crops. Relying on manual agricultural management not only has low work efficiency and large workload, but also cannot effectively monitor crop water demand for a long time, which is not conducive to scientific management of irrigation and the promotion of advanced irrigation technology.
随着我国水资源供需矛盾日益尖锐，农业用水配额减少的问题日益突出，采用低能耗的以滴灌、喷灌、微灌为代表的自动化节水灌溉技术得到了迅速推广及应用，农业自动化灌溉系统由传统的充分灌溉向非充分灌溉转变。通过对灌区资源进行自动化控制和优化配置，可以大大提高农业灌溉用水的利用率，缓解我国水资源紧缺的现状。With the increasingly acute contradiction between supply and demand of water resources in my country, the problem of reducing agricultural water quotas has become increasingly prominent. The use of low-energy-consumption automated water-saving irrigation technologies represented by drip irrigation, sprinkler irrigation, and micro-irrigation has been rapidly promoted and applied. Agricultural automatic irrigation systems are composed of Transformation from traditional full irrigation to inadequate irrigation. Through the automatic control and optimal allocation of irrigation area resources, the utilization rate of agricultural irrigation water can be greatly improved, and the current situation of water shortage in my country can be alleviated.
发明内容SUMMARY OF THE INVENTION
有鉴于此，本发明提供一种智能灌溉管理系统，用以解决现有技术中存在的问题，可根据不同土壤与气候情况，针对不同种类农作物的各生育阶段，通过灌溉用水需求模型计算出需要灌水量，反馈调节用水信息进行灌溉的智能灌溉管理系统。In view of this, the present invention provides an intelligent irrigation management system to solve the problems existing in the prior art. According to different soil and climate conditions, for each growth stage of different types of crops, the irrigation water demand model can be used to calculate the demand. An intelligent irrigation management system for irrigating by feeding back and adjusting the amount of water used for irrigation.
本发明采用以下技术方案：The present invention adopts following technical scheme:
一种智能灌溉管理系统，其中，包括智能感知平台、无线传输平台、云数据中心和应用管理平台；所述智能感知平台包括数据采集控制器、LoRa传输模块、数据采集模块与控制终端模块；所述数据采集模块包括土壤墒情传感器、土壤温度传感器、水位传感器、气象环境传感器；所述控制终端模块包括水泵和电磁阀，所述电磁阀为多个，所述多个电磁阀均与数据采集控制器无线连接；所述无线传输平台包括GPRS网络和4G网络；所述云数据中心包括云服务器、灌溉用水需求模型、作物需水预报与灌溉预报；所述灌溉用水需求模型根据智能感知平台中数据采集模块采集到的土壤墒情、土壤温度、水位、气象信息自动计算，发布作物需水预报与灌溉预报；所述应用管理平台包括灌溉管理软件和用户终端，所述用户终端包含PC端与手机端。An intelligent irrigation management system, including an intelligent perception platform, a wireless transmission platform, a cloud data center and an application management platform; the intelligent perception platform includes a data acquisition controller, a LoRa transmission module, a data acquisition module and a control terminal module; The data acquisition module includes a soil moisture sensor, a soil temperature sensor, a water level sensor, and a meteorological environment sensor; the control terminal module includes a water pump and a solenoid valve, and the solenoid valves are multiple, and the multiple solenoid valves are all related to the data acquisition control. The wireless transmission platform includes GPRS network and 4G network; the cloud data center includes cloud server, irrigation water demand model, crop water demand forecast and irrigation forecast; the irrigation water demand model is based on the data in the intelligent perception platform The soil moisture, soil temperature, water level, and meteorological information collected by the acquisition module are automatically calculated, and the crop water demand forecast and irrigation forecast are released; the application management platform includes irrigation management software and a user terminal, and the user terminal includes a PC terminal and a mobile terminal. .
优选的，所述智能感知平台包括数据采集控制器、LoRa传输模块、数据采集模块与控制终端模块；所述数据采集模块用于采集不同深度土壤水分含量数据、不同深度土壤温度数据、地下水位数据、大气温度、大气湿度、实施风速、光照强度等数据；所述LoRa传输模块将数据采集模块采集到的数据信息通过LoRa技术无线传输至数据采集控制器。Preferably, the intelligent perception platform includes a data acquisition controller, a LoRa transmission module, a data acquisition module and a control terminal module; the data acquisition module is used to collect soil moisture content data at different depths, soil temperature data at different depths, and groundwater level data , atmospheric temperature, atmospheric humidity, implementation wind speed, light intensity and other data; the LoRa transmission module wirelessly transmits the data information collected by the data acquisition module to the data acquisition controller through LoRa technology.
优选的，所述无线传输平台将数据采集控制器收集到的数据，通过GPRS网络或4G网络远程传输至云数据中心中的云服务器。Preferably, the wireless transmission platform remotely transmits the data collected by the data acquisition controller to the cloud server in the cloud data center through a GPRS network or a 4G network.
优选的，所述云服务器将通过无线传输平台接收所述智能感知平台采集到的信息，自动输入所述灌溉用水需求模型；所述灌溉用水需求模型根据接收到的信息和预设的作物参数生成灌溉预报，并传输至应用管理平台。Preferably, the cloud server will receive the information collected by the intelligent perception platform through the wireless transmission platform, and automatically input the irrigation water demand model; the irrigation water demand model is generated according to the received information and preset crop parameters Irrigation forecasts are transmitted to the application management platform.
所述灌溉预报包括：预测土壤含水量θi随时间的变化，当土壤含水量下降到适宜含水量下限时，由土壤田间持水量与含水量下限值间的差结合作物计划湿润层湿度，计算获得作物单次灌溉需水量，即灌水定额；最后根据特定灌溉区域内不同作物种植面积，计算获得区域灌溉需水量。The irrigation forecast includes: predicting the change of soil water content θ i with time, when the soil water content drops to the lower limit of suitable water content, the difference between the soil field water holding capacity and the lower limit of water content is combined with the humidity of the planned wet layer of the crop, Calculate the water demand for a single irrigation of crops, that is, the irrigation quota; finally, according to the planting area of different crops in a specific irrigation area, calculate and obtain the regional irrigation water demand.
所述作物单次灌溉需水量预测公式如下：The formula for predicting the water demand for single irrigation of the crops is as follows:
式中，II为各类作物单次灌溉需水量，单位：m3/亩；θf为田间持水量；θi为预测土壤含水量；γ为土壤容重，单位：g/cm3，根据实测获取；Hi为特定生育阶段内计划湿润层深度，单位：m，根据当地作物估算。In the formula, II is the single irrigation water demand of various crops, unit: m 3 /mu; θ f is the field water capacity; θ i is the predicted soil water content; γ is the soil bulk density, unit: g/cm 3 , according to Obtained by actual measurement; Hi is the planned wet layer depth in a specific growth stage, unit: m, estimated according to local crops.
所述预测土壤含水量θi的计算公式为：The calculation formula of the predicted soil water content θ i is:
式中，θi-1为上一时段土壤含水量；ETi-1为作物日耗水量(mm/d)；Ri-1为计算时段内有效降雨量(mm)，可用气象预报数据；ΔW为计划湿润层增加而增加的水量(mm)，根据已有研究成果结合当地作物估算；Fi-1为土壤深层渗漏量(mm)，取0；H为计划湿润层深度(mm)，根据当地作物估算；γ为土壤容重，单位：g/cm3；Gi-1为作物利用地下水量。In the formula, θ i-1 is the soil water content in the previous period; ET i-1 is the daily water consumption of crops (mm/d); R i-1 is the effective rainfall in the calculation period (mm), and meteorological forecast data can be used; ΔW is the amount of water added by the planned increase in wet layer (mm), estimated according to the existing research results and local crops; F i-1 is the amount of leakage in the deep soil layer (mm), which is taken as 0; H is the depth of the planned wet layer (mm) , estimated according to local crops; γ is soil bulk density, unit: g/cm 3 ; G i-1 is the amount of groundwater utilized by crops.
优选的，所述上一时段土壤含水量θi-1由计算机根据定点实测土壤墒情值与其对应的影像像元属性值拟合求出，计算机程序自动调用拟合函数得到拟和方程，选取相关系数R方最大的拟合函数进行计算确定。Preferably, the soil water content θ i-1 in the previous period is calculated by a computer according to the measured soil moisture value at a fixed point and its corresponding image pixel attribute value, and the computer program automatically calls the fitting function to obtain the fitting equation, and selects the relevant The fitting function with the largest coefficient R square is calculated and determined.
所述ETi-1为作物日耗水量是利用参考腾发量ET0和作物系数kc计算；所述ET0通过以下公式进行计算：Described ET i-1 is crop daily water consumption is to utilize reference evapotranspiration ET 0 and crop coefficient kc to calculate; Described ET 0 is calculated by the following formula:
优选的，上述式中a、b、c均为待定系数，设置为可输入变量；Tmax、Tmin分别为当日最高、最低气，从上述数据采集模块采集的气象环境传感器中数据；J为日序数，如1月12日，J＝12；T为下一日平均温度，从上述数据采集模块采集的气象环境传感器中数据。Preferably, in the above formula, a, b, and c are all undetermined coefficients, which are set as input variables; T max and T min are respectively the highest and lowest gas of the day, which are collected from the meteorological environment sensor data collected by the above data acquisition module; J is the The daily serial number, such as January 12, J=12; T is the average temperature of the next day, from the data collected by the above-mentioned data acquisition module from the meteorological environment sensor.
该方法创新性的将传统的基于多个气象参数的计算方法简化为只需输入降水量、最高气温、最低气温三个参数，极大的减轻的灌溉预报中面临的气象参数获取难、类型多、输入工作量大等问题。This method innovatively simplifies the traditional calculation method based on multiple meteorological parameters to only need to input three parameters: precipitation, maximum temperature and minimum temperature, which greatly reduces the difficulty in obtaining meteorological parameters and many types of meteorological parameters in irrigation forecasting. , input workload and other issues.
当计算出的预测土壤含水量θi＞土壤灌溉临界点θk时，灌溉用水需求模型自动判断无需灌溉，则返回模型继续监测。当计算出的预测土壤含水量θi＜土壤灌溉临界点θk时，灌溉用水需求模型自动判断需要灌溉，此时通过下述公式计算预测出区域灌溉需水量：When the calculated predicted soil water content θ i > the soil irrigation critical point θ k , the irrigation water demand model automatically judges that irrigation is not required, and returns to the model to continue monitoring. When the calculated predicted soil water content θ i < the soil irrigation critical point θ k , the irrigation water demand model automatically determines that irrigation is required. At this time, the regional irrigation water demand is calculated and predicted by the following formula:
式中Wt为名称为t的计算区域灌溉需水量；At为名称为t的计算区域的面积，该面积通过遥感技术对区域作物种植结构进行目视解译与监督分类来计算，由计算机软件自我学习、判断确定；Ii为第i旬的灌溉水量。In the formula, W t is the irrigation water demand of the calculation area named t; A t is the area of the calculation area named t, which is calculated by visual interpretation and supervised classification of the regional crop planting structure through remote sensing technology, and is calculated by computer The software learns and judges by itself; I i is the amount of irrigation water in the ith tenth day.
优选的，所述应用管理平台根据接收到的灌溉预报，由灌溉管理软件生成相应的灌溉策略，所述灌溉策略通过远程传输至数据采集控制器，再通过LoRa传输模块传输至控制终端模块，并且同时将灌溉策略发送至用户终端，用户可在PC端与手机端同时查看；控制终端模块根据接收到的命令，打开或关闭水泵与电磁阀。Preferably, the application management platform generates a corresponding irrigation strategy by the irrigation management software according to the received irrigation forecast, the irrigation strategy is remotely transmitted to the data acquisition controller, and then transmitted to the control terminal module through the LoRa transmission module, and At the same time, the irrigation strategy is sent to the user terminal, and the user can view it on the PC terminal and the mobile terminal at the same time; the control terminal module turns on or off the water pump and solenoid valve according to the received command.
优选的，控制终端模块采用无线阀门控制器。所述无线阀门控制器包括控制器壳体，所述控制器壳体上设置有天线和支架，所述控制器壳体上设置有太阳能电池板，所述控制器壳体内设置有锂电池、升压模块、储能电路、阀门控制继电器、DC-DC模块、MCU和LoRa无线通信模块，所述太阳能电池板与锂电池电连接，为所述锂电池充电；所述锂电池分别与所述升压模块和DC-DC模块电连接，为所述升压模块和DC-DC模块供电；所述升压模块、储能电路、阀门控制继电器依次电连接，所述阀门控制继电器、LoRa无线通信模块均与所述MCU电连接；所述天线与LoRa无线通信模块连接。Preferably, the control terminal module adopts a wireless valve controller. The wireless valve controller includes a controller casing, an antenna and a bracket are arranged on the controller casing, a solar panel is arranged on the controller casing, and a lithium battery, a liter battery are arranged in the controller casing. voltage module, energy storage circuit, valve control relay, DC-DC module, MCU and LoRa wireless communication module, the solar panel is electrically connected to the lithium battery to charge the lithium battery; the lithium battery is connected to the The booster module and the DC-DC module are electrically connected to supply power to the booster module and the DC-DC module; the booster module, the energy storage circuit, and the valve control relay are electrically connected in sequence, and the valve control relay, the LoRa wireless communication module Both are electrically connected to the MCU; the antenna is connected to the LoRa wireless communication module.
所述灌溉管理软件不仅可以根据智能感知平台采集到的数据通过灌溉用水需求模型自动生成灌溉策略，也可以通过用户终端人工制定灌溉策略；所述人工制定灌溉策略包括水泵与电磁阀打开时间、开启个数与灌水量。The irrigation management software can not only automatically generate an irrigation strategy through the irrigation water demand model according to the data collected by the intelligent perception platform, but also manually formulate the irrigation strategy through the user terminal; number and amount of irrigation.
本发明的有益效果为：The beneficial effects of the present invention are:
本发明提供一种智能灌溉管理系统，通过灌溉用水需求模型自动生成最佳灌溉策略，能够更加合理、科学的利用水资源，避免水资源浪费；本发明实现自动控制的智能灌溉，极大提高了劳动生产力和减低了劳动成本。本发明能够实现不同深度土壤水分、不同深度土壤温度、地下水位、大气温度、大气湿度、实施风速、光照强度等数据的自动采集与传输，不仅节省了人工实地测量的工作量，也保证了数据的连续；通过将现场灌溉状态上传到互联网平台，可以实时远程监控运行状态；能够人工制定灌溉策略，避免因数据采集或传输发生故障而不能进行自动灌溉的情况发生。The invention provides an intelligent irrigation management system, which can automatically generate an optimal irrigation strategy through an irrigation water demand model, can utilize water resources more rationally and scientifically, and avoid waste of water resources; the invention realizes automatic control of intelligent irrigation, which greatly improves the Labor productivity and reduced labor costs. The invention can realize automatic collection and transmission of data such as soil moisture at different depths, soil temperatures at different depths, groundwater level, atmospheric temperature, atmospheric humidity, implementation wind speed, light intensity, etc., which not only saves the workload of manual field measurement, but also ensures data Continuously; by uploading the on-site irrigation status to the Internet platform, the operation status can be remotely monitored in real time; irrigation strategies can be formulated manually to avoid the situation that automatic irrigation cannot be performed due to data collection or transmission failures.
本发明提供了一种作物日耗水量ETi-1的计算方法，该方法公式所需输入参数仅为当日最高、最低气温与下一日平均温度，这些数据都能可以从气象站与天气预报中简单获取，简化原作物日耗水量通用公式—Penman-Montieth方程所需的参数种类与计算过程。该系统能够根据实时监测到的土壤墒情、土壤温度、气象信息，远程传输至云服务器中，结合作物生长需求，通过灌溉用水需求模型计算出需要灌水量，自动制定浇灌策略，控制灌溉，实现个性化浇灌。The invention provides a method for calculating the daily water consumption ET i-1 of crops. The input parameters required by the formula of the method are only the highest and lowest air temperature of the current day and the average temperature of the next day. These data can be obtained from weather stations and weather forecasts. It can be easily obtained from the original crop, and the parameter types and calculation process required by the Penman-Montieth equation, the general formula for the daily water consumption of the original crops, are simplified. The system can remotely transmit the real-time monitoring of soil moisture, soil temperature, and meteorological information to the cloud server. Combined with crop growth needs, the system can calculate the required irrigation amount through the irrigation water demand model, automatically formulate irrigation strategies, and control irrigation to achieve individuality. chemical watering.
附图说明Description of drawings
图1是本发明的方法流程图；Fig. 1 is the method flow chart of the present invention;
图2是无线阀门控制器的结构示意图。Figure 2 is a schematic structural diagram of a wireless valve controller.
图3是无线阀门控制器的结构框图。Figure 3 is a structural block diagram of the wireless valve controller.
图4是无线阀门控制器MCU模块的电路原理图。Figure 4 is the circuit schematic diagram of the wireless valve controller MCU module.
图5是无线阀门控制器升压电路原理图。Figure 5 is the schematic diagram of the booster circuit of the wireless valve controller.
图6是无线阀门控制器太阳能充电电路原理图。Figure 6 is a schematic diagram of the solar charging circuit of the wireless valve controller.
图7是无线阀门控制器阀门控制继电器1路脉冲阀电路原理图。Figure 7 is a schematic diagram of the wireless valve controller valve control relay 1-way pulse valve circuit.
图8是无线阀门控制器阀门控制继电器2路脉冲阀电路原理图。Figure 8 is a schematic diagram of the wireless valve controller valve control relay 2-way pulse valve circuit.
图中：1-控制器壳体；2-太阳能电池板；3-天线；4-支架；5-接线孔；101-应用管理平台；102-云数据中心；103-无线传输平台；104-智能感知平台。In the figure: 1-controller housing; 2-solar panel; 3-antenna; 4-support; 5-connection hole; 101-application management platform; 102-cloud data center; 103-wireless transmission platform; 104-intelligence Perception platform.
具体实施方式Detailed ways
如图1所示，本发明提供一种智能灌溉管理系统，包括智能感知平台104、无线传输平台103、云数据中心102和应用管理平台101；所述智能感知平台包括数据采集控制器、LoRa传输模块、数据采集模块与控制终端模块；所述数据采集模块包括土壤墒情传感器、土壤温度传感器、水位传感器、气象环境传感器；所述控制终端模块包括水泵和电磁阀，所述电磁阀为多个，所述多个电磁阀均与数据采集控制器无线连接；所述无线传输平台包括GPRS网络和4G网络；所述云数据中心包括云服务器、灌溉用水需求模型、作物需水预报与灌溉预报；所述灌溉用水需求模型根据智能感知平台中数据采集模块采集到的土壤墒情、土壤温度、水位、气象信息自动计算，发布作物需水预报与灌溉预报；所述应用管理平台包括灌溉管理软件和用户终端，所述用户终端包含PC端与手机端。As shown in FIG. 1, the present invention provides an intelligent irrigation management system, including an intelligent perception platform 104, a wireless transmission platform 103, a cloud data center 102 and an application management platform 101; the intelligent perception platform includes a data acquisition controller, LoRa transmission module, a data acquisition module and a control terminal module; the data acquisition module includes a soil moisture sensor, a soil temperature sensor, a water level sensor, and a meteorological environment sensor; the control terminal module includes a water pump and a solenoid valve, and the solenoid valves are multiple, The multiple solenoid valves are wirelessly connected to the data acquisition controller; the wireless transmission platform includes a GPRS network and a 4G network; the cloud data center includes a cloud server, an irrigation water demand model, crop water demand forecast and irrigation forecast; The irrigation water demand model is automatically calculated according to the soil moisture, soil temperature, water level, and meteorological information collected by the data acquisition module in the intelligent perception platform, and the crop water demand forecast and irrigation forecast are released; the application management platform includes irrigation management software and user terminals. , the user terminal includes a PC terminal and a mobile terminal.
智能感知平台包括数据采集控制器、LoRa传输模块、数据采集模块与控制终端模块；所述数据采集模块用于采集不同深度土壤水分含量数据、不同深度土壤温度数据、地下水位数据、大气温度、大气湿度、实施风速、光照强度等数据；所述LoRa传输模块将数据采集模块采集到的数据信息通过LoRa技术无线传输至数据采集控制器。The intelligent perception platform includes a data acquisition controller, a LoRa transmission module, a data acquisition module and a control terminal module; the data acquisition module is used to collect soil moisture content data at different depths, soil temperature data at different depths, groundwater level data, atmospheric temperature, atmospheric Humidity, implementation wind speed, light intensity and other data; the LoRa transmission module wirelessly transmits the data information collected by the data acquisition module to the data acquisition controller through LoRa technology.
在一个实施例中，无线传输平台将数据采集控制器收集到的数据，通过GPRS网络或4G网络远程传输至云数据中心中的云服务器。In one embodiment, the wireless transmission platform remotely transmits the data collected by the data acquisition controller to the cloud server in the cloud data center through the GPRS network or the 4G network.
在一个实施例中，云服务器将通过无线传输平台接收所述智能感知平台采集到的信息，自动输入所述灌溉用水需求模型；所述灌溉用水需求模型根据接收到的信息和预设的作物参数生成灌溉预报，并传输至应用管理平台。In one embodiment, the cloud server will receive the information collected by the intelligent perception platform through the wireless transmission platform, and automatically input the irrigation water demand model; the irrigation water demand model is based on the received information and preset crop parameters Irrigation forecasts are generated and transmitted to the application management platform.
所述灌溉预报包括：预测土壤含水量θi随时间的变化，当土壤含水量下降到适宜含水量下限时，由土壤田间持水量与含水量下限值间的差结合作物计划湿润层湿度，计算获得作物单次灌溉需水量，即灌水定额；最后根据特定灌溉区域内不同作物种植面积，计算获得区域灌溉需水量。The irrigation forecast includes: predicting the change of soil water content θ i with time, when the soil water content drops to the lower limit of suitable water content, the difference between the soil field water holding capacity and the lower limit of water content is combined with the humidity of the planned wet layer of the crop, Calculate the water demand for a single irrigation of crops, that is, the irrigation quota; finally, according to the planting area of different crops in a specific irrigation area, calculate and obtain the regional irrigation water demand.
所述作物单次灌溉需水量预测公式如下：The formula for predicting the water demand for single irrigation of the crops is as follows:
式中，II为各类作物单次灌溉需水量，单位：m3/亩；θf为田间持水量；θi为预测土壤含水量；γ为土壤容重，单位：g/cm3，根据实测获取；Hi为特定生育阶段内计划湿润层深度，单位：m，根据当地作物估算。In the formula, II is the single irrigation water demand of various crops, unit: m 3 /mu; θ f is the field water capacity; θ i is the predicted soil water content; γ is the soil bulk density, unit: g/cm 3 , according to Obtained by actual measurement; Hi is the planned wet layer depth in a specific growth stage, unit: m, estimated according to local crops.
所述预测土壤含水量θi的计算公式为：The calculation formula of the predicted soil water content θ i is:
式中，θi-1为上一时段土壤含水量；ETi-1为作物日耗水量(mm/d)；Ri-1为计算时段内有效降雨量(mm)，可用气象预报数据；ΔW为计划湿润层增加而增加的水量(mm)，根据已有研究成果结合当地作物估算；Fi-1为土壤深层渗漏量(mm)，取0；H为计划湿润层深度(mm)，根据当地作物估算；γ为土壤容重，单位：g/cm3；Gi-1为作物利用地下水量。In the formula, θ i-1 is the soil water content in the previous period; ET i-1 is the daily water consumption of crops (mm/d); R i-1 is the effective rainfall in the calculation period (mm), and meteorological forecast data can be used; ΔW is the amount of water added by the planned increase in wet layer (mm), estimated according to the existing research results and local crops; F i-1 is the amount of leakage in the deep soil layer (mm), which is taken as 0; H is the depth of the planned wet layer (mm) , estimated according to local crops; γ is soil bulk density, unit: g/cm 3 ; G i-1 is the amount of groundwater utilized by crops.
优选的，所述上一时段土壤含水量θi-1由计算机根据定点实测土壤墒情值与其对应的影像像元属性值拟合求出，计算机程序自动调用拟合函数得到拟和方程，选取相关系数R方最大的拟合函数进行计算确定。Preferably, the soil moisture content θ i-1 in the previous period is calculated by a computer according to the measured soil moisture value at a fixed point and its corresponding image pixel attribute value, and the computer program automatically calls the fitting function to obtain the fitting equation, and selects the relevant The fitting function with the largest coefficient R square is calculated and determined.
该方法借助遥感手段结合实测数据计算区域范围内不同计算单元土壤墒情变化情况。系统使用Landsat8的相关波段栅格数据来获取系统所需的灌区的初始土壤含水率的信息，然后将卫星影像进行辐射校正、大气校正和图像增强、数据融合等操作，来消除卫星成像过程中受到的影响、提高影像分辨率，如卫星速度变化、大气与地物反射与发射电磁波的相互作用、随机噪声、可见光波段与全色波段融合等。经过对所得的卫星图像的处理后，由影像的相关波段计算区域的归一化植被指数(NDVI)，再由归一化植被指数计算温度植被干旱指数(TVDI)，建立TVDI与实地监测土壤含水率两者之间的相关关系。This method uses remote sensing means and measured data to calculate the changes of soil moisture in different calculation units in the area. The system uses the relevant band raster data of Landsat8 to obtain the information of the initial soil moisture content of the irrigation area required by the system, and then performs radiation correction, atmospheric correction, image enhancement, data fusion and other operations on the satellite image to eliminate the influence of the satellite imaging process. The influence of the image is improved, and the image resolution is improved, such as the change of satellite speed, the interaction between the reflection of the atmosphere and ground objects and the emission of electromagnetic waves, random noise, the fusion of visible light band and panchromatic band, etc. After processing the obtained satellite images, the normalized vegetation index (NDVI) of the region is calculated from the relevant bands of the image, and then the temperature vegetation drought index (TVDI) is calculated from the normalized vegetation index to establish TVDI and field monitoring of soil moisture. relationship between the two rates.
通过卫星影像获取的灌区当前土壤含水率的栅格数据是由一个个的像元组成，像元的大小取决于影像的分辨率，每一个像元代表组成灌区的一块面积，因为现在Landsat8的分辨率可以达到15m，所以假定每一个像元内的当前土壤含水率是一样的，这样每一个像元为一基本计算单元，相当于对灌区进行离散化，即单元格剖分。然后进行单元特性分析，即通过卫星影像栅格数据可以知道像元内当前土壤含水率。The raster data of the current soil moisture content in the irrigation area obtained from satellite images is composed of pixels, the size of which depends on the resolution of the image, and each pixel represents an area of the irrigation area, because the resolution of Landsat8 now Therefore, it is assumed that the current soil moisture content in each pixel is the same, so that each pixel is a basic calculation unit, which is equivalent to discretizing the irrigation area, that is, cell division. Then, the unit characteristic analysis is carried out, that is, the current soil moisture content in the pixel can be known through the satellite image raster data.
所述ETi-1为作物日耗水量是利用参考腾发量ET0和作物系数kc计算。本发明为减轻模型使用人员的工作量，将ET0预测模型及作物系数、土壤系数的计算和预测方法带入Penman-Montieth方程，可确定出参考腾发量ET0的计算模型。所述ET0通过以下公式进行计算：The ET i-1 is the daily water consumption of crops, which is calculated by using the reference evapotranspiration ET 0 and the crop coefficient kc. In order to reduce the workload of model users, the invention brings the ET 0 prediction model and the calculation and prediction method of crop coefficient and soil coefficient into the Penman-Montieth equation to determine the calculation model of the reference evapotranspiration ET 0 . The ET 0 is calculated by the following formula:
优选的，上述式中a、b、c均为待定系数，设置为可输入变量；Tmax、Tmin分别为当日最高、最低气，从上述数据采集模块采集的气象环境传感器中数据；J为日序数，如1月12日，J＝12；T为下一日平均温度，从上述数据采集模块采集的气象环境传感器中数据。Preferably, in the above formula, a, b, and c are all undetermined coefficients, which are set as input variables; T max and T min are respectively the highest and lowest gas of the day, which are collected from the meteorological environment sensor data collected by the above data acquisition module; J is the The daily serial number, such as January 12, J=12; T is the average temperature of the next day, from the data collected by the above-mentioned data acquisition module from the meteorological environment sensor.
当计算出的预测土壤含水量θi＞土壤灌溉临界点θk时，灌溉用水需求模型自动判断无需灌溉，则返回模型继续监测。当计算出的预测土壤含水量θi＜土壤灌溉临界点θk时，灌溉用水需求模型自动判断需要灌溉，此时通过下述公式计算预测出区域灌溉需水量：When the calculated predicted soil water content θ i > the soil irrigation critical point θ k , the irrigation water demand model automatically judges that irrigation is not required, and returns to the model to continue monitoring. When the calculated predicted soil water content θ i < the soil irrigation critical point θ k , the irrigation water demand model automatically determines that irrigation is required. At this time, the regional irrigation water demand is calculated and predicted by the following formula:
式中Wt为名称为t的计算区域灌溉需水量；At为名称为t的计算区域的面积，该面积通过遥感技术对区域作物种植结构进行目视解译与监督分类来计算，由计算机软件自我学习、判断确定；Ii为第i旬的灌溉水量。In the formula, W t is the irrigation water demand of the calculation area named t; A t is the area of the calculation area named t, which is calculated by visual interpretation and supervised classification of the regional crop planting structure through remote sensing technology, and is calculated by computer The software learns and judges by itself; I i is the amount of irrigation water in the ith tenth day.
应用管理平台根据接收到的灌溉预报，由灌溉管理软件生成相应的灌溉策略，所述灌溉策略通过远程传输至数据采集控制器，再通过LoRa传输模块传输至控制终端模块，并且同时将灌溉策略发送至用户终端，用户可在PC端与手机端同时查看；控制终端模块根据接收到的命令，打开或关闭水泵与电磁阀。The application management platform generates the corresponding irrigation strategy by the irrigation management software according to the received irrigation forecast. The irrigation strategy is transmitted to the data acquisition controller remotely, and then transmitted to the control terminal module through the LoRa transmission module, and the irrigation strategy is sent at the same time. To the user terminal, the user can view it on the PC and mobile terminals at the same time; the control terminal module opens or closes the water pump and solenoid valve according to the received command.
灌溉管理软件不仅可以根据智能感知平台采集到的数据通过灌溉用水需求模型自动生成灌溉策略，也可以通过用户终端人工制定灌溉策略；所述人工制定灌溉策略包括水泵与电磁阀打开时间、开启个数与灌水量。The irrigation management software can not only automatically generate irrigation strategies through the irrigation water demand model according to the data collected by the intelligent perception platform, but also manually formulate irrigation strategies through the user terminal; with the amount of irrigation.
本发明的智能感知平台通过土壤墒情传感器、土壤温度传感器、水位传感器采集墒情、温度和水位信息，气象环境传感器采集现场的气象环境信息，由数据采集控制器控制土壤墒情传感器、土壤温度传感器、水位传感器和气象环境传感器进行信息的采集，采集到的信息通过LoRa传输模块传输至数据采集控制器。通过无线传输平台的GPRS网络、4G网络等将信息发送给云数据中心的云服务器，云数据中心根据采集到的信息和预设的灌溉用水需求模型生成作物需水预报和灌溉预报，并传输给灌溉管理软件，由灌溉管理软件生成相应的灌溉策略，由智能终端控制灌溉管理软件根据灌溉策略打开或关闭电磁阀，通过电磁阀的打开或关闭控制水泵的浇灌。The intelligent perception platform of the present invention collects moisture, temperature and water level information through soil moisture sensor, soil temperature sensor and water level sensor, the meteorological environment sensor collects on-site meteorological environment information, and the data acquisition controller controls the soil moisture sensor, soil temperature sensor and water level Sensors and meteorological environment sensors collect information, and the collected information is transmitted to the data acquisition controller through the LoRa transmission module. The information is sent to the cloud server of the cloud data center through the GPRS network and 4G network of the wireless transmission platform. The cloud data center generates crop water demand forecast and irrigation forecast according to the collected information and the preset irrigation water demand model, and transmits it to Irrigation management software, the irrigation management software generates the corresponding irrigation strategy, and the intelligent terminal controls the irrigation management software to open or close the solenoid valve according to the irrigation strategy, and control the watering of the water pump through the opening or closing of the solenoid valve.
如图2-图8所示，在一个实施例中，控制终端模块采用无线阀门控制器。无线阀门控制器包括控制器壳体1、太阳能电池板2、天线3和支架4，控制器壳体1上设置有天线3、支架4和太阳能电池板2，控制器壳体1内设置有锂电池、升压模块、储能电路、阀门控制继电器、DC-DC模块、MCU和LoRa无线通信模块，太阳能电池板2与锂电池电连接，为所述锂电池充电；锂电池分别与升压模块和DC-DC模块电连接，为升压模块和DC-DC模块供电；升压模块、储能电路、阀门控制继电器依次电连接，阀门控制继电器、LoRa无线通信模块均与所述MCU电连接；天线3与LoRa无线通信模块连接。支架4上设置有连接脉冲阀的接线孔5，支架为圆柱体金属支架，在支架上设置有防腐涂层。As shown in Figures 2-8, in one embodiment, the control terminal module adopts a wireless valve controller. The wireless valve controller includes a controller housing 1, a solar panel 2, an antenna 3 and a bracket 4. The controller housing 1 is provided with an antenna 3, a bracket 4 and a solar panel 2. The controller housing 1 is provided with lithium Battery, booster module, energy storage circuit, valve control relay, DC-DC module, MCU and LoRa wireless communication module, the solar panel 2 is electrically connected to the lithium battery to charge the lithium battery; the lithium battery is connected to the booster module respectively It is electrically connected to the DC-DC module to supply power to the booster module and the DC-DC module; the booster module, the energy storage circuit, and the valve control relay are electrically connected in sequence, and the valve control relay and the LoRa wireless communication module are all electrically connected to the MCU; The antenna 3 is connected to the LoRa wireless communication module. The bracket 4 is provided with a wiring hole 5 for connecting the pulse valve, the bracket is a cylindrical metal bracket, and an anti-corrosion coating is arranged on the bracket.
如图4所示，MCU为STM8L152C8T6芯片。如图7、图8所示，阀门控制继电器包括1路脉冲阀电路和2路脉冲阀电路。1路脉冲阀电路包括电容C16、二极管D5、继电器S1、电阻R15、R13、三极管Q2、电阻R17、电阻R19、三极管Q4、二极管D7、D9、D11、继电器S3，电容C16的阴极接地、阳极接二极管D5的负极，电容C16、二极管D5的负极和继电器S1的线圈共同接12V电压，二极管D5的正极、继电器S1共同连接到三极管Q2的集电极上，电阻R15一端接地，另一端与电阻R13共同连接到三极管Q2的基极，电阻R13另一端接MCU的H2+信号线，三极管Q2的发射极接地。二极管D7的正极接地，负极接继电器S1的常闭开关，继电器S1的常闭开关接地；继电器S1的常开开关接12V电压。二极管D9的正极接地，负极接继电器S3的常闭开关，继电器S3的常闭开关接地，常开开关接12V电压。二极管D11的负极与继电器S1的线圈共同连接至12V电压，二极管D11与继电器S1并联，二极管D11的正极接三极管Q4的集电极，三极管Q4的发射极接地，基极分别连接电阻R17、R19的一端，电阻R17的另一端接MCU的H2-信号端，电阻R19的另一端接地。As shown in Figure 4, the MCU is the STM8L152C8T6 chip. As shown in Figure 7 and Figure 8, the valve control relay includes 1-way pulse valve circuit and 2-way pulse valve circuit. 1-channel pulse valve circuit includes capacitor C16, diode D5, relay S1, resistor R15, R13, transistor Q2, resistor R17, resistor R19, transistor Q4, diode D7, D9, D11, relay S3, the cathode of capacitor C16 is grounded, the anode is connected to The cathode of the diode D5, the cathode of the capacitor C16, the cathode of the diode D5 and the coil of the relay S1 are connected to 12V voltage together, the anode of the diode D5 and the relay S1 are connected to the collector of the transistor Q2, one end of the resistor R15 is grounded, and the other end is connected to the resistor R13. Connect to the base of the transistor Q2, the other end of the resistor R13 is connected to the H2+ signal line of the MCU, and the emitter of the transistor Q2 is grounded. The anode of diode D7 is grounded, the cathode is connected to the normally closed switch of relay S1, the normally closed switch of relay S1 is grounded; the normally open switch of relay S1 is connected to 12V voltage. The anode of diode D9 is grounded, the cathode is connected to the normally closed switch of relay S3, the normally closed switch of relay S3 is grounded, and the normally open switch is connected to 12V voltage. The cathode of the diode D11 and the coil of the relay S1 are connected to the 12V voltage. The diode D11 is connected in parallel with the relay S1. , the other end of the resistor R17 is connected to the H2-signal end of the MCU, and the other end of the resistor R19 is grounded.
2路脉冲阀电路包括二极管D6、继电器S2、电阻R14、R16、三极管Q3、电阻R18、电阻R20、三极管Q5、二极管D8、D10、D12、继电器S4。电阻R14一端连接H1+信号端，另一端分别连接电阻R16的一端和三极管Q3的基极，电阻R16另一端和三极管Q3的发射极接地。三极管Q3的集电极与继电器S2的线圈连接，二极管D6与继电器S2并联，二极管D6的负极接12V电压，继电器S2的常开开关接12V电压，常闭开关分别接地和二极管D8的负极，二极管D8的正极接地。二极管D12与继电器S4并联，二极管D12的负极接12V电压，二极管D12的正极接三极管Q5的集电极，三极管Q5的发射极接地，基极分别接电阻R18和R20的一端，电阻R18的另一端接H1-信号端，电阻R20的另一端接地。继电器S4的常开开关接12V电压，常闭开关接地。电阻D10的负极接继电器S4的常闭开关，正极接地。The 2-way pulse valve circuit includes diode D6, relay S2, resistors R14, R16, transistor Q3, resistor R18, resistor R20, transistor Q5, diode D8, D10, D12, and relay S4. One end of the resistor R14 is connected to the H1+ signal terminal, the other end is respectively connected to one end of the resistor R16 and the base of the transistor Q3, and the other end of the resistor R16 and the emitter of the transistor Q3 are grounded. The collector of the transistor Q3 is connected to the coil of the relay S2, the diode D6 is connected in parallel with the relay S2, the cathode of the diode D6 is connected to the 12V voltage, the normally open switch of the relay S2 is connected to the 12V voltage, the normally closed switch is grounded respectively, and the cathode of the diode D8, the diode D8 The positive pole is grounded. The diode D12 is connected in parallel with the relay S4, the cathode of the diode D12 is connected to the 12V voltage, the anode of the diode D12 is connected to the collector of the transistor Q5, the emitter of the transistor Q5 is connected to the ground, the base is connected to one end of the resistors R18 and R20 respectively, and the other end of the resistor R18 is connected H1-signal terminal, the other terminal of resistor R20 is grounded. The normally open switch of relay S4 is connected to 12V voltage, and the normally closed switch is grounded. The negative pole of the resistor D10 is connected to the normally closed switch of the relay S4, and the positive pole is grounded.
无线阀门控制器的LoRa无线通信模块将接收到的信号解析后送MCU，MCU处理后下发开或关阀的指令，这时候后面的升压、储能、继电器等电路协同工作发出正/反向的脉冲从而控制脉冲阀工作。在正常工作状态下，用户可根据环境监测数据通过控制中心下发控制命令，由无线阀门控制器控制阀门的打开和关闭，当无线阀门控制器在成功执行完控制命令后会返回阀门的工作状态，若控制中心在10秒左右没有接收到设备的返回命令，则说明命令未能成功执行，这时可再次下发命令。无线阀门控制器在正常状态下会通过LoRa无线通信模块定时上传实时环境数据和阀门状态。The LoRa wireless communication module of the wireless valve controller parses the received signal and sends it to the MCU. After the MCU processes it, it issues an instruction to open or close the valve. At this time, the circuits behind booster, energy storage, relay and other circuits work together to issue positive/negative The pulse in the direction controls the pulse valve to work. In normal working state, the user can issue control commands through the control center according to the environmental monitoring data, and the wireless valve controller will control the opening and closing of the valve. When the wireless valve controller successfully executes the control command, it will return to the working state of the valve , if the control center does not receive the return command from the device in about 10 seconds, it means that the command has not been successfully executed, and the command can be issued again. Under normal conditions, the wireless valve controller will regularly upload real-time environmental data and valve status through the LoRa wireless communication module.
本发明大大优化了现有灌溉系统架构，极大节省了硬件成本的投入，在每个灌溉节点设置对应的电磁阀，通过水泵的入口处的电磁阀实现智能灌溉。通过气象环境传感器对现场数据采集，制定系统科学的灌溉方案。通过将现场各传感器采集到的数据以及灌溉状态上传到互联网平台，可以实时远程监控运行状态。根据采集到的数据通过灌溉用水需求模型，生成作物需水预报和灌溉预报，判断是否进行灌溉，以及计算灌溉强度是多大。本发明的灌溉预报包括灌溉启动时间，灌溉时间，灌溉次数，水量等。The present invention greatly optimizes the existing irrigation system structure, greatly saves the investment of hardware cost, sets a corresponding electromagnetic valve at each irrigation node, and realizes intelligent irrigation through the electromagnetic valve at the inlet of the water pump. Collect on-site data through meteorological environmental sensors, and formulate a systematic and scientific irrigation plan. By uploading the data collected by the sensors on site and the irrigation status to the Internet platform, the operation status can be remotely monitored in real time. According to the collected data, through the irrigation water demand model, the crop water demand forecast and the irrigation forecast are generated, and it is judged whether to irrigate, and the irrigation intensity is calculated. The irrigation forecast of the present invention includes irrigation start time, irrigation time, irrigation times, water quantity and the like.
本发明的整个灌溉控制过程在应用管理平台上通过移动终端上的灌溉管理软件进行远程控制，通过无线方式远程对电磁阀和数据采集控制器进行控制，利用无线传输平台在云服务器上进行数据交互。本发明实现了对田间气象参数和灌溉参数的实时采集。The entire irrigation control process of the present invention is remotely controlled by the irrigation management software on the mobile terminal on the application management platform, the solenoid valve and the data acquisition controller are remotely controlled by wireless means, and data interaction is performed on the cloud server by using the wireless transmission platform . The invention realizes the real-time collection of field meteorological parameters and irrigation parameters.
以上所述仅为本发明的较佳实施例，并不用以限制本发明，凡在本发明的精神和原则之内，所作的任何修改、等同替换、改进等，均应包含在本发明的保护范围之内。The above are only preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included in the protection of the present invention. within the range.
Claims (7)
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910363189.3A CN110050673A (en) | 2019-04-30 | 2019-04-30 | A kind of intelligent irrigation management system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910363189.3A CN110050673A (en) | 2019-04-30 | 2019-04-30 | A kind of intelligent irrigation management system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN110050673A true CN110050673A (en) | 2019-07-26 |
Family
ID=67321994
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910363189.3A Pending CN110050673A (en) | 2019-04-30 | 2019-04-30 | A kind of intelligent irrigation management system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110050673A (en) |
Cited By (23)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110432122A (en) * | 2019-09-05 | 2019-11-12 | 湖南人文科技学院 | Gardens are irrigated and gardens water body integrated synthesis cyclic control system and method |
| CN110471478A (en) * | 2019-08-29 | 2019-11-19 | 厦门海洋职业技术学院 | A kind of wisdom fisheries management system of 4G |
| CN110689173A (en) * | 2019-09-12 | 2020-01-14 | 黄河水利委员会黄河水利科学研究院 | Irrigation area agricultural irrigation water demand decision method and system |
| CN110738196A (en) * | 2019-11-13 | 2020-01-31 | 云南农业大学 | real-time irrigation forecasting system based on regional soil moisture content monitoring and remote sensing data |
| CN110754346A (en) * | 2019-09-24 | 2020-02-07 | 杜驾麟 | Automatic control device based on electrical system |
| CN110754330A (en) * | 2019-11-29 | 2020-02-07 | 石河子大学 | IoT intelligent water-saving irrigation system based on LoRa technology |
| CN110810222A (en) * | 2019-11-08 | 2020-02-21 | 山东新元易方科技有限公司 | Intelligent monitoring control instrument and control method |
| CN111142483A (en) * | 2019-12-16 | 2020-05-12 | 深圳市东深电子股份有限公司 | Irrigation area big data acquisition management system and method based on water affair Internet of things |
| CN111561972A (en) * | 2020-06-18 | 2020-08-21 | 华南农业大学 | A system and method for predicting soil moisture content based on time series |
| CN111667376A (en) * | 2020-06-19 | 2020-09-15 | 黄河勘测规划设计研究院有限公司 | Irrigation district water conservation management system based on big dipper navigation communication technology |
| CN112400676A (en) * | 2020-10-26 | 2021-02-26 | 安徽工程大学 | Intelligent irrigation system based on big data |
| CN112730800A (en) * | 2020-12-14 | 2021-04-30 | 云南俊联科技有限公司 | Online measuring method for field water holding capacity |
| CN112772385A (en) * | 2021-01-29 | 2021-05-11 | 天津市科睿思奇智控技术有限公司 | Full-automatic remote irrigation system |
| CN112913654A (en) * | 2021-03-19 | 2021-06-08 | 西华大学 | Intelligent irrigation system and method for fritillaria cirrhosa |
| CN113141940A (en) * | 2021-06-01 | 2021-07-23 | 中国农业科学院蔬菜花卉研究所 | Intelligent water precise irrigation control system and method for fruit and vegetable cultivation in sunlight greenhouse |
| CN113207651A (en) * | 2021-01-21 | 2021-08-06 | 深圳市芯中芯科技有限公司 | Park intelligent watering system based on 4G network |
| CN113491192A (en) * | 2020-04-08 | 2021-10-12 | 雪川农业发展股份有限公司 | Intelligent water and fertilizer integrated management system for field potato planting |
| CN113875561A (en) * | 2021-10-22 | 2022-01-04 | 广东电网有限责任公司 | Intelligent irrigation system |
| CN113951115A (en) * | 2021-11-28 | 2022-01-21 | 石河子大学 | Cotton field irrigation Internet of things monitoring system based on LoRa |
| CN115250889A (en) * | 2022-08-29 | 2022-11-01 | 安徽工业大学 | An Automatic Irrigation System Based on DQN Algorithm |
| CN115777505A (en) * | 2022-11-28 | 2023-03-14 | 江苏大学 | An adaptive intelligent irrigation system and method applying Internet of Things technology |
| CN116135008A (en) * | 2021-11-17 | 2023-05-19 | 扬州智水物联网有限公司 | An intelligent irrigation valve system and cloud platform control method |
| CN116406606A (en) * | 2023-04-20 | 2023-07-11 | 广州上诺生物技术有限公司 | Intelligent irrigation system |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR101416296B1 (en) * | 2013-01-25 | 2014-07-14 | (주)에스이랩 | Intelligent irrigation control system and controlling method thereof |
| CN104521699A (en) * | 2014-11-18 | 2015-04-22 | 华北水利水电大学 | Field intelligent irrigation on-line control management method |
| CN106780086A (en) * | 2016-12-15 | 2017-05-31 | 新疆水利水电科学研究院 | A kind of irrigation water management system and management method based on Farmland Water monitoring |
| EP3179319A1 (en) * | 2015-12-10 | 2017-06-14 | Sysman Progetti & Servizi S.r.l. | Method for irrigation planning and system for its implementation |
| CN109169186A (en) * | 2018-08-21 | 2019-01-11 | 江苏大学 | A kind of hills crop irrigation system and method based on Internet of Things |
-
2019
- 2019-04-30 CN CN201910363189.3A patent/CN110050673A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR101416296B1 (en) * | 2013-01-25 | 2014-07-14 | (주)에스이랩 | Intelligent irrigation control system and controlling method thereof |
| CN104521699A (en) * | 2014-11-18 | 2015-04-22 | 华北水利水电大学 | Field intelligent irrigation on-line control management method |
| EP3179319A1 (en) * | 2015-12-10 | 2017-06-14 | Sysman Progetti & Servizi S.r.l. | Method for irrigation planning and system for its implementation |
| CN106780086A (en) * | 2016-12-15 | 2017-05-31 | 新疆水利水电科学研究院 | A kind of irrigation water management system and management method based on Farmland Water monitoring |
| CN109169186A (en) * | 2018-08-21 | 2019-01-11 | 江苏大学 | A kind of hills crop irrigation system and method based on Internet of Things |
Non-Patent Citations (8)
| Title |
|---|
| 亢庆: "《南方岩溶区水土资源监测关键技术与应用》", 31 December 2016, 黄河水利出版社, pages: 382 - 385 * |
| 景明;王军涛;程献国;高子乐;: "基于改进Valiantzas方程的黄河下游柳园口灌区ET_0预测研究", 干旱地区农业研究, no. 02, 10 March 2018 (2018-03-10), pages 273 - 278 * |
| 景明;程献国;王军涛;姜晗琳;: "黄河下游灌区引黄灌溉需水预测关键技术分析", 水资源与水工程学报, no. 06, 15 December 2013 (2013-12-15), pages 60 - 63 * |
| 李志然;潘鹤立;尚春雨;潘东明;: "基于物联网智慧农业的作物水肥一体化系统设计与应用", 福建农业科技, no. 03, 28 March 2019 (2019-03-28), pages 58 - 65 * |
| 李志然;潘鹤立;尚春雨;潘东明;: "基于物联网智慧农业的作物水肥一体化系统设计与应用", 福建农业科技, no. 03, pages 58 - 65 * |
| 王军涛;景明;程献国;张霞;: "基于GIS的引黄灌区用水需求预报系统研究", 节水灌溉, no. 03, 5 March 2015 (2015-03-05), pages 66 - 75 * |
| 王军涛;景明;程献国;张霞;: "基于GIS的引黄灌区用水需求预报系统研究", 节水灌溉, no. 03, pages 66 - 75 * |
| 王灿;王中华;王冬雪;李猛;李岳炀;: "基于LoRa的智能灌溉系统设计", 计算机测量与控制, no. 08 * |
Cited By (25)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110471478A (en) * | 2019-08-29 | 2019-11-19 | 厦门海洋职业技术学院 | A kind of wisdom fisheries management system of 4G |
| CN110432122A (en) * | 2019-09-05 | 2019-11-12 | 湖南人文科技学院 | Gardens are irrigated and gardens water body integrated synthesis cyclic control system and method |
| CN110689173A (en) * | 2019-09-12 | 2020-01-14 | 黄河水利委员会黄河水利科学研究院 | Irrigation area agricultural irrigation water demand decision method and system |
| CN110754346A (en) * | 2019-09-24 | 2020-02-07 | 杜驾麟 | Automatic control device based on electrical system |
| CN110810222A (en) * | 2019-11-08 | 2020-02-21 | 山东新元易方科技有限公司 | Intelligent monitoring control instrument and control method |
| CN110810222B (en) * | 2019-11-08 | 2021-11-02 | 山东华特智慧科技有限公司 | Intelligent monitoring controller and control method |
| CN110738196A (en) * | 2019-11-13 | 2020-01-31 | 云南农业大学 | real-time irrigation forecasting system based on regional soil moisture content monitoring and remote sensing data |
| CN110754330A (en) * | 2019-11-29 | 2020-02-07 | 石河子大学 | IoT intelligent water-saving irrigation system based on LoRa technology |
| CN111142483A (en) * | 2019-12-16 | 2020-05-12 | 深圳市东深电子股份有限公司 | Irrigation area big data acquisition management system and method based on water affair Internet of things |
| CN113491192A (en) * | 2020-04-08 | 2021-10-12 | 雪川农业发展股份有限公司 | Intelligent water and fertilizer integrated management system for field potato planting |
| CN111561972A (en) * | 2020-06-18 | 2020-08-21 | 华南农业大学 | A system and method for predicting soil moisture content based on time series |
| CN111667376A (en) * | 2020-06-19 | 2020-09-15 | 黄河勘测规划设计研究院有限公司 | Irrigation district water conservation management system based on big dipper navigation communication technology |
| CN112400676A (en) * | 2020-10-26 | 2021-02-26 | 安徽工程大学 | Intelligent irrigation system based on big data |
| CN112400676B (en) * | 2020-10-26 | 2023-02-28 | 安徽工程大学 | A smart irrigation system based on big data |
| CN112730800A (en) * | 2020-12-14 | 2021-04-30 | 云南俊联科技有限公司 | Online measuring method for field water holding capacity |
| CN113207651A (en) * | 2021-01-21 | 2021-08-06 | 深圳市芯中芯科技有限公司 | Park intelligent watering system based on 4G network |
| CN112772385A (en) * | 2021-01-29 | 2021-05-11 | 天津市科睿思奇智控技术有限公司 | Full-automatic remote irrigation system |
| CN112913654A (en) * | 2021-03-19 | 2021-06-08 | 西华大学 | Intelligent irrigation system and method for fritillaria cirrhosa |
| CN113141940A (en) * | 2021-06-01 | 2021-07-23 | 中国农业科学院蔬菜花卉研究所 | Intelligent water precise irrigation control system and method for fruit and vegetable cultivation in sunlight greenhouse |
| CN113875561A (en) * | 2021-10-22 | 2022-01-04 | 广东电网有限责任公司 | Intelligent irrigation system |
| CN116135008A (en) * | 2021-11-17 | 2023-05-19 | 扬州智水物联网有限公司 | An intelligent irrigation valve system and cloud platform control method |
| CN113951115A (en) * | 2021-11-28 | 2022-01-21 | 石河子大学 | Cotton field irrigation Internet of things monitoring system based on LoRa |
| CN115250889A (en) * | 2022-08-29 | 2022-11-01 | 安徽工业大学 | An Automatic Irrigation System Based on DQN Algorithm |
| CN115777505A (en) * | 2022-11-28 | 2023-03-14 | 江苏大学 | An adaptive intelligent irrigation system and method applying Internet of Things technology |
| CN116406606A (en) * | 2023-04-20 | 2023-07-11 | 广州上诺生物技术有限公司 | Intelligent irrigation system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110050673A (en) | A kind of intelligent irrigation management system | |
| CN104904569B (en) | A kind of intelligent irrigation regulator control system and method based on the estimation of dynamic water content | |
| CN110214506A (en) | Liquid manure management-control method and system | |
| CN104460582B (en) | A kind of Internet of Things intelligent irrigation fertilising control method and system based on fuzzy control | |
| CN211960395U (en) | A modern agricultural precision irrigation system | |
| CN206165346U (en) | Remote visualization intelligence irrigation system based on thing networking | |
| CN112136667B (en) | An intelligent sprinkler irrigation method and system based on edge machine learning | |
| CN106035003A (en) | Water saving and control intelligent management method for regulating and controlling paddy field non-point source pollution | |
| CN108156918A (en) | A kind of scale farmland wireless internet of things Intelligent drip irrigation system and method | |
| US11457576B2 (en) | Intelligent irrigation system | |
| CN109452146A (en) | Water-saving Irrigation of Winter Wheat decision-making technique, control device and control system | |
| CN207612812U (en) | A kind of Internet of Things control irrigation unit | |
| CN109601334A (en) | Liquid manure drip irrigation system based on Internet of Things | |
| CN110741914A (en) | Rice field automatic water-saving irrigation system and method based on recurrent neural network | |
| CN115104515B (en) | A cloud computing method, cloud computing platform and irrigation terminal for irrigation decision-making based on maximizing rainfall utilization | |
| CN113115694A (en) | Modern agricultural precise irrigation system and irrigation method thereof | |
| CN108713481B (en) | Photovoltaic metering pump valve intelligent system | |
| CN101836573A (en) | System and method for farmland intelligent-control water distribution management | |
| CN116746463A (en) | An intelligent watering system based on weather forecast and soil monitoring | |
| Li et al. | Design of rice intelligent water-saving irrigation system based on agricultural internet of things | |
| CN206674701U (en) | A kind of intelligent tea place automatic irrigation system | |
| CN209879355U (en) | Water-saving irrigation control management system | |
| CN115804336A (en) | Rice field water-saving irrigation system suitable for flowing irrigation district certainly | |
| CN213069619U (en) | Greening area management and control system based on Internet of things | |
| CN106818419A (en) | A kind of water-fertilizer-pesticide integrated control method with Changes in weather |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20190726 |
|
| RJ01 | Rejection of invention patent application after publication |