With the rapid advancement of science and technology, the concept of "scientific farming" has become increasingly popular among farmers and agricultural professionals. The use of advanced technologies in sowing, fertilizing, and irrigation has proven to be an effective way to reduce costs while increasing productivity. Traditionally, scientific farming relied on technicians visiting rural areas to disseminate knowledge, which was inefficient and limited in reach. To address these challenges, agricultural expert systems were developed, allowing farmers to access expert advice through computer software and knowledge-based reasoning. Although this approach improved efficiency, it introduced new issues such as complex user interfaces and inaccuracies from manually entered data.
In terms of the current status of agricultural expert systems both domestically and internationally, China began developing such systems in the 1990s. For example, in 1992, Zhao Shuangning from the Chinese Academy of Agricultural Sciences created the "Winter Wheat New Variety Breeding Expert System." In 1998, Nanjing Agricultural University developed an intelligent decision support system for agricultural management. By 2003, Zheng Xiangqun and Gao Huaiyou had applied data mining techniques to analyze agricultural environmental information.
Globally, the concept of precision agriculture was introduced in the early 1980s by the United States. Today, in developed countries like the U.S., precision agriculture has evolved into a high-tech industry that is widely recognized as a key driver for sustainable farming. This approach leverages spatial and temporal variations in farmland conditions to implement precise crop management strategies. For instance, fertilizer application can vary based on soil fertility levels—more in low-fertility areas and less in high-fertility ones.
Japan is also one of the early adopters of agricultural expert systems, with significant government support leading to the development of several practical systems. Examples include the Tomato Cultivation Management Expert Consultation System at the University of Tokyo, the Nutrient Solution Management Expert System, and various disease diagnosis and crop management support systems developed by Chiba University using the MICCS tool.
Despite these advancements, most regions outside North America have not yet fully adopted precision agriculture due to high costs and technological limitations. However, the potential benefits remain clear, and ongoing research continues to push the boundaries of what is possible.
The goal of this study is to develop a portable intelligent agricultural system based on the AVR32 AT32UC3A microcontroller. The system consists of two main components: a handheld terminal and a wireless sensor network. The wireless sensors collect environmental data using a DS18B20 temperature sensor, and the data is transmitted via an NRF24L01 module to the AVR32 board. Once activated, the system automatically gathers data and processes it using a built-in fuzzy inference system. The results are then displayed on the handheld interface, offering an intuitive and user-friendly experience. The system is compact, powerful, and easily upgradable, making it ideal for field use.
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