Melon growth management expert system based on Internet of Things

Abstract

The invention provides a melon growth management expert system based on the Internet of Things. The melon growth management expert system comprises a main interface module, an expert knowledge base module, a monitoring information module, a growth simulation and prediction module, a decision-making and inference module, an expert consultation module, a personal information module and a backgroundmaintenance module. The melon growth management expert system manages melon real-time growth environment monitoring, growth status monitoring, water and fertilizer amount and environmental temperatureearly-warning as well as pest and disease damage judgment combined with an image recognition technology, realizes melon growth and development simulation and yield quality prediction, and is equippedwith a planting knowledge base and an expert online question answering function. The melon growth management expert system realizes real-time monitoring of environment and plant growth information, is conductive to planting decision-making, reminds the user to improve the management conditions through real-time water and fertilizer amount and environmental temperature early-warning, realizes high-precision simulation of plant growth indexes, fruit quality and yield, and provides real-time water and fertilizer precise decision-making scheme according to comprehensive analysis of real-time environment and plant growth monitoring, data processing based on a machine learning method, plant growth model prediction and the like.

Description

technical field [0001] The invention relates to the field of agricultural technology, in particular to an Internet of Things-based melon growth management expert system. Background technique [0002] my country is a big country that grows melons in the world, but the yield per unit area is far from that of developed countries, and its yield and quality potential are far from the optimal level. Among them, the precise management and application of water and fertilizer play an important role in many factors that affect the yield and quality of melons. plays a central role. The lack of experience of agricultural growers leads to the lack of scientific and quantitative decision-making on water and fertilizer management and temperature of melons, and there is no consulting support from professionals in the process of production activities, which makes it difficult to solve various planting problems and reduce production. Simple and visualized solutions are urgently needed. The ex...

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Problems solved by technology

[0004] (1) The data knowledge owned by the system cannot be updated. Many expert management systems only use past climate information and differences in cultivated varieties to reason and make decisions. Even most systems are stand-alone versions that cannot accumulate and update data

[0005] (2) The system lacks the artificial intelligence AI part. At present, AI technology has developed to rely on the deep structure artificial neural network model and deep learning stage, and can be applied to all aspects of life, but it is rarely used in agriculture. For example, it can be used through Artificial intelligence realizes the intelligent identification and management of pests and diseases, artificial intelligence identifies the growth status of crops, and makes decisions on water, fertilizer management and temperature based on the current phenotype indicators of crops

[0006] (3) Agricultural Internet of Things technology is not used. At present, the Internet of Things is developing rapidly, but there are very few related agricultural applications. Data can be transmitted to the Internet of Things through sensors, real-time data information can be transmitted to the system, and real-time corrections and correlations can be made to system decisions. early warning

[0007] (4) The functions are scattered and there is no whole-process management. At present, there are only some scattered software such as temperature monitoring, pest decision-making and other functions, which cannot help users make decisions in the whole process. The user makes the right decision, solves the user's problem

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