Abstract:

With the development of agricultural modernization, traditional irrigation methods can no longer meet the demands of agricultural development. Especially, agricultural water use is still facing water resource shortages and other situations. However, intelligent irrigation technology can well achieve the rational utilization of water resources, thereby enhancing productivity and realizing sustainable agricultural development. The intelligent irrigation algorithm is the core to ensure the efficient operation and intelligence of the intelligent irrigation system. The algorithm relies on sensor technology to collect data, transmits it through wireless communication, and uses machine learning and neural networks to analyze big data to achieve precise irrigation. However, intelligent irrigation algorithms still face multiple challenges in terms of data quality, privacy protection and algorithm complexity. This paper discussed and put forward some insights on improving data quality, optimizing algorithms and implementing policy support, in order to promote the wide application of intelligent irrigation, provide certain guidance for the development direction of intelligent irrigation algorithms, and achieve agricultural modernization and sustainable development.

Key words: intelligent irrigation algorithm, model, machine learning, data analysis and processing