Design and realization of intelligent service system for monitoring and warning of meteorological disasters in facility agriculture in North China

Abstract: In recent years, facility agriculture that features high-efficiency has become an important part of agricultural production in the North of China. However, it was suffered some damages from severe weather such as cold wave, strong winds, blizzards, low temperature and less sunshine hazard. This study was aimed to cater for the straight-through demands of facility agricultural breeding enterprises and large agricultural breeding families for facility Agra-meteorological disasters resisting and early warning. Based on artificial intelligence means such as internet data mining and expert knowledge decision-making system, we established an intelligent service system for monitoring and warning of meteorological disasters in facility agriculture to guarantee the security and stability of facility agriculture production. First of all, the meteorological knowledge that was urgently needed for the production of crops such as cucumber, strawberry, tomato, and sweet pepper etc. was summarized by using information technologies such as cloud computing, Internet of things, mobile Internet, the Java EE technology framework, SOA(service oriented architecture) cloud service technology, and multi-factor association rule learning method. Then we defined the rules of agricultural meteorological disaster warning and production management expert knowledge based on the location-based weather forecasting data, microclimate environment data of facility agriculture, dynamic planting information and growth period data of facility crops, which would effectively improve the integration of intelligent services and actual production needs. Finally, the facility Agra-meteorological disaster monitoring and early warning and intelligent decision-making pushing service system was built depending on the integrated platform for intelligent grid weather forecast and warning of meteorological department, forecast of refined meteorological elements in the next 3 to 7 days, Internet data mining and expert knowledge decision techniques, which would provide interactive, individualized, intelligent and straight-through meteorological information service for agricultural parks and large farming households. It indicated that real-time warning of meteorological disasters and intelligent decision-making services for production management had been working well. The system could not only provide real-time, personalized guidance for production practices, but also realize automatic warnings for Agra-meteorological disasters in major Northern facility agriculture such as cold wave, strong wind, low temperature and less sunshine hazard, and heavy snow. It would timely send information on the important turning weather in next 7 days, meteorological disaster warning, facility agricultural production management decision-making, and disaster prevention recommendations to agricultural technicians through smart phone APP. It was convenient for production managers to pay attention to weather changes and adopt corresponding production management measures according to the type of planting crops in time. Therefore, they would be in early preparation for meteorological disasters, avoiding major disaster losses. Providing interactive, personalized and intelligent straight-through meteorological information services for agricultural parks and large agricultural breeding families would effectively solve the pre-disaster early warning and disaster prevention problems of major facilities agricultural meteorological disasters. It would significantly improve the efficiency of modern agricultural production and be of far-reaching significance for promoting the development of agricultural modernization and modern agriculture.