Design And Realization Of IOT-based Diagnosis And Management System For Wheat Production

Wheat is one of the most important grain crops in China. But due to the tremendous changes ofclimate condition in its long growing period, it is vulnerable to a variety of meteorological disasters,which seriously impact on its production. Therefore, it is important for raising the level of scientificmanagement of wheat production, through timely grasping the environment changes, strengtheningaccurate monitoring for various meteorological disasters, and optimizing the wheat productionmanagement scheme according to the growth of the wheat In order to improve the diagnosisperformance for wheat growth, the diagnosis and management system for wheat production based onInternet of things is designed and implemented.This system is achieved based on the previous research. The critical data associated with the growthof wheat and meteorological disasters (including HD image, video etc.) is obtained accurately andtransmitted steadily to the network database through the integration of heterogeneous network, such asthe wireless sensor network, wireless local area networks (Wi-Fi), mobile wireless communicationnetwork (GPRS/3G) and the Internet. On the server side, the system can provide decision supportingservices for making final intelligent diagnosis of wheat growth status and disasters with combination ofnetwork database, statistical algorithm, computer control and inference engine etc. according to themonitoring data and characteristics of the crops and meteorological condition.The diagnosis and prediction part of this system is a B/S structural program running on the server,developed by C#language under.NET environment. It’s designed with the3-tier application framework,specifically data layer, logic layer and the presentation layer, for data acquisition, data receiving, datastorage, data processing and diagnosis. By such optimal methods, advantages of the system are ensuredin keeping excellent object-oriented functions, better compatibility and suitable systematicstandardization in follow-up development.The system consists of six modules individually for data acquisition, knowledge specification andnormalization, intelligent diagnosis and analysis, user management, assistant help for systemmanagement and application, those of which are mainly responsible for receiving real-time data fromremote sites, knowledge specification and normalization, definition of the diagnosis indexes for crop andmeteorological disasters, etc. By utility of monitoring data combined with crop and meteorological indexspecification, the system may give precision and rapid diagnosis of condition and probability for bothwheat growth and main meteorological disasters, which includes drought and waterlogging, lowtemperature, dry and hot wind. In order for precision diagnosis of wheat growth and development,4grades are classified according to the crucial factors below: numbers of leaf on main stem, numbers ofstems and tillers per plant, numbers of secondary roots and tillers, those parameters are obtained fromfield experiments or knowledge and experiences from different agricultural experts.The results of diagnosis and decision supporting services can be output in multiple forms, like MSword document, different type of curves and figures, as well as data sheet depending on user’s option. With integration of web services and socket techniques, users can easily get the multi-source dataresources and information services via the platforms, such as mobile terminals, LED screens, flat pad,personal computers, etc. Demonstration and actual application of the system has been successivelycarried out in the main wheat production regions of China, and the results show a quite significantprospect in remote intelligent management and precision monitoring diversification of meteorologicaldisasters by integration of IOT technology.