Abstract
Greenhouse is an important part of facility agriculture and a typical application scenario of modern agricultural technology. The greenhouse environment has the characteristics of nonlinearity, strong coupling, large inertia, and multiple disturbances. There are many environmental factors and it is a typical complex system [7]. In smart greenhouses, control commands are mostly triggered by complex events with multi-dimensional information. In this paper, by building the aggregation structure of complex events in the greenhouse, the technology is applied in the greenhouse as a whole. The core innovations of this paper are as follows: through the analysis of the information transmission process in the greenhouse, combined with the characteristics of the scene, a CEP information structure with predictive modules is formed, which is conducive to the popularization and application of CEP technology in the agricultural field. Pointed out the importance of extreme conditions in the prediction of the greenhouse environment for model evaluation. By improving the loss function in the machine learning algorithm, the prediction performance of a variety of algorithms under this condition has been improved. Applying CEP technology to intelligent greenhouse control scenarios, a set of practical complex event processing systems for greenhouse control has been formed.
Highlights
Control commands generated by the systemThe information generated by the system to inform workers that the environment is far from equilibrium The information generated by the system to inform the worker that the controller connection is interrupted The information generated by the system to inform workers of plant growth statusTable2
This paper solves the key problem of the greenhouse control engine construction in the CEP system, provides a complete greenhouse event aggregation scheme, realizes the greenhouse complex event processing system based on the automata algorithm and the expert system rules, and well integrates the current greenhouse Predicting, formulating planting plans, decoupling, human-machine coordination control plans and their scheduling strategies, early warning and Internet of Things monitoring and other common areas of knowledge and methods, fully combining the advantages of various control methods to control the characteristics of greenhouses, and coordinating with each other
It has good interpretability and an easier optimization strategy, which realizes the efficient control of man-machine coordination
Summary
CEP (complex event processing technology) is derived from active database technology [12] and is an important method to solve the problem of multiple sequential event stream processing [13]. It can make full use of information from different angles to make decisions on the current situation and has powerful asynchronous decoupling. The decision-making method mainly depends on the connection method of EPA (Event Processing Agent) and the realization of EPA aggregation logic. There are very few applications of complex event processing in the field of greenhouse control
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