44results about How to "Increased ability to process dynamic information" patented technology

The invention discloses a greenhouse environment multi-parameter intelligent monitoring system based on the Internet of Things. The system is composed of a watermelon greenhouse environment parameteracquisition platform based on a ZigBee network and a watermelon greenhouse environment microclimate factor evaluation subsystem. The system realizes intelligent detection of watermelon greenhouse environment temperature and evaluation of microclimate environment factors. The problems that an existing watermelon greenhouse environment monitoring system does not accurately detect watermelon greenhouse environment parameters and evaluate environment factors according to the characteristics of nonlinearity, large lag, complex greenhouse environment parameter changes and the like of greenhouse environment parameter changes, and therefore the accuracy of predicting and evaluating the watermelon greenhouse parameters is improved are effectively solved.

The invention discloses an intelligent tomato greenhouse temperature early-warning system based on a minimum vector machine. The early-warning system is characterized by being composed of a tomato greenhouse environmental parameter acquisition and intelligent prediction platform based on a CAN field bus and an intelligent tomato greenhouse temperature early-warning system. By means of the intelligent tomato greenhouse temperature early-warning system based on the minimum vector machine in the invention, many problems still in the environment in a closed tomato greenhouse due to the reasons ofunreasonable design, backward equipment, incomplete control system and the like in the traditional tomato greenhouse environment can be effectively solved; and furthermore, the control problem that the tomato greenhouse environment temperature is greatly influenced due to the fact that the existing tomato greenhouse environment monitoring system does not monitor and predict the temperature in thetomato greenhouse environment according to the characteristics of nonlinearity and large lag of tomato greenhouse environmental temperature change, large tomato greenhouse area, complex temperature change and the like can be effectively solved.

The invention discloses an intelligent orchard yield prediction system based on Internet of Things. The intelligent orchard yield prediction system consists of an apple orchard environment parameter collection platform and an apple orchard environment yield prediction subsystem, and achieves the detection of apple orchard environment microclimate parameters and the prediction of the yield. The apple orchard environment monitoring system effectively solves the problems that an existing apple orchard environment monitoring system does not accurately detect the apple orchard environment temperature and predict the yield according to the characteristics of nonlinearity, large lag, complex change and the like of the apple orchard environment temperature change, so that the accuracy and robustness of predicting the apple orchard environment temperature and yield are improved.

The invention discloses an aquaculture pond dissolved oxygen detection device. The device is characterized in that a detection system is composed of two parts including an aquaculture pond environmentwater quality parameter acquisition platform based on a wireless sensor network, and a pond dissolved oxygen intelligent early warning system. The device provided by the invention effectively solvesa problem of great influence on aquaculture pond dissolved oxygen detection caused by lack of detecting the dissolved oxygen of the existing aquaculture pond according to the characteristics, such asnonlinearity and great lag of change of pound dissolved oxygen and large area and complex change of dissolved oxygen of the aquaculture pond.

The invention discloses a dust concentration intelligent detection system which is composed of a dust concentration environmental parameter acquisition platform based on a CAN bus and a dust concentration intelligent prediction module. The dust concentration environmental parameter acquisition platform based on the CAN bus realizes detection and adjustment of dust concentration environmental factor parameters. The dust concentration intelligent prediction module is composed of a dust concentration interval number neural network model, an interval number prediction model and an interval numberCMAC cerebellar neural network dust concentration fusion model. The system effectively solves the problems that the existing industrial and agricultural production environment does not have the characteristics of nonlinearity, large lag, complex dynamic change and the like according to the change of the dust concentration, and the dust concentration cannot be accurately detected and predicted, sothat the effective management of the dust concentration of the industrial and agricultural production environment is greatly influenced.

The invention discloses an eggplant greenhouse environment intelligent detection system based on wavelet neural network, which is characterized in that: the detection system is composed of two parts: an eggplant greenhouse environment parameter collection platform based on a wireless sensor network and an eggplant greenhouse output intelligent early warning system; The present invention effectively solves the problem that the output of the existing eggplant greenhouse is not affected by the non-linearity, large lag, large area of ​​the eggplant greenhouse, and complex temperature changes of the eggplant greenhouse. The precise detection and adjustment of temperature will greatly affect the environmental yield prediction and production management of eggplant greenhouses.

The invention discloses an intelligent detection device for eggplant greenhouse temperature based on DRNN neural network, which is characterized in that: the detection device is composed of two parts: an eggplant greenhouse environment parameter acquisition platform based on CAN bus and an eggplant greenhouse temperature intelligent detection system; The invention effectively solves the problem that the existing eggplant greenhouse monitoring system does not detect the temperature of the eggplant greenhouse environment according to the characteristics of nonlinearity, large lag, and complex temperature changes of the eggplant greenhouse environment, which greatly affects the eggplant greenhouse environment. Regulation of ambient temperature.

The invention discloses an intelligent detection system for building energy consumption, which is characterized in that: the system is composed of two parts: a building energy consumption parameter collection platform based on a wireless sensor network and a building energy consumption level classification system, and is based on a wireless sensor network The building energy consumption parameter acquisition platform realizes the detection and monitoring of the environmental parameters affecting the building. The building energy consumption level classification system consists of a temperature detection module, an illuminance detection module, a humidity detection module, an energy consumption prediction module and an interval number kohonen neural network building Composition of material energy consumption state classifiers; the present invention effectively solves the characteristics of existing building energy consumption that is not changed according to building environmental factors, such as nonlinearity, large lag, and complex changes affecting building energy consumption, and intelligently monitors building energy consumption. This will greatly affect the accuracy of building detection.

The invention discloses a multi-point fire early warning system based on the Internet of Things. The system is composed of a ZigBee network-based gas station oil tank area environmental parameter acquisition platform and a gas station oil tank area environment multi-point fire early warning subsystem; The environmental multi-point fire early warning subsystem of the oil tank area of ​​the gas station is composed of multiple parameter detection units and multiple HRFNN fuzzy recursive neural network fire early warning classifiers; The environmental parameters of the oil tank area of ​​the gas station are characterized by nonlinearity, large lag, and complex changes in the environmental parameters of the oil tank area of ​​the gas station. The environmental parameters of the oil tank area of ​​the gas station are accurately detected and the fire warning is carried out, so as to improve the prediction of the fire parameters of the gas station and Fire accuracy issues.

The invention discloses a fish pond water quality intelligent monitoring system, which is characterized in that: the fish pond water quality parameter detection platform based on a wireless sensor network and a fish pond output intelligent prediction system are composed of two parts; the invention effectively solves the problem of the prior art Only rely on equipment to monitor fish pond water quality parameters, only obtain fish pond water quality parameters, but there is no problem of effectively predicting fish pond production according to the impact of fish pond water quality on fish pond production.

The invention discloses a large data detection system for foundation pits. The system is composed of two parts: a foundation pit parameter acquisition platform and a foundation pit parameter big data processing subsystem. Engineering safety and reliability management level; the present invention effectively solves the influence of the existing foundation pit on the safety of the foundation pit due to the non-linearity, large lag and complex change of the parameters of the large foundation pit area without changing the parameters of the foundation pit. Prediction and early warning of foundation pit safety will greatly affect the safety management of foundation pits.

The invention discloses a greenhouse environment multi-parameter intelligent monitoring system based on the Internet of Things. The system is composed of a ZigBee network-based watermelon greenhouse environment parameter collection platform and a watermelon greenhouse environment microclimate factor evaluation subsystem. The system realizes watermelon greenhouse environment monitoring. The intelligent detection of ambient temperature and the evaluation of microclimate environmental factors; the present invention effectively solves the characteristics that the existing watermelon greenhouse environment monitoring system does not change according to the greenhouse environment parameters, such as nonlinearity, large lag, and complex changes in greenhouse environment parameters. Parameters are accurately detected and environmental factors are evaluated, so as to improve the accuracy of prediction and evaluation of watermelon greenhouse parameters.

The invention discloses a multi-point temperature sensor intelligent monitoring system based on a field bus network. The system is composed of an apple orchard environmental parameter acquisition platform and an apple orchard environmental temperature evaluation subsystem. The system realizes intelligent detection and monitoring of the apple orchard environmental temperature. Evaluate the temperature; the present invention effectively solves the problem that the existing apple orchard environmental monitoring is not based on the characteristics of non-linearity, large lag, and large apple orchard area and complex temperature changes of the apple orchard environmental temperature change, and intelligently monitors the temperature of the apple orchard environment The monitoring problem with forecasting, which greatly affects the ambient temperature of apple orchards.