Today, the agriculture industry has been developing intellectualization and automation proactively for reducing labor force and increase yields. In the past, farmers usually followed the rule of thumb to grow crops; however, due to the dramatic climate change, it becomes harder for farmers to cope with it by merely following the rule of thumb, which leads to crop damage. Therefore, it is vital to input scientific data development and technology for optimizing the environment parameters of crops and further enhance the yields. Additionally, many farms need to spread pesticides to avoid pests and diseases; yet, too much pesticide may cause soil alkalization. To enrich the growing-power of the lands, farmers will fertilize the lands; nevertheless, too much of it will also cause soil acidification, which will need to leave the land fallow to improve the soil quality. The study provides an intelligent agriculture system based on LSTM. The system develops an Internet of Things (IoT) to monitor the environmental conditions of soil, sunlight, and temperature; additionally, the research combines the information from the Central Weather Bureau for predicting the timing for watering and notifying farmers about the suggested amount of pesticides and fertilizers. The features of this article are as follows: 1. Build a clustering tree of crops according to the adaptability; 2. Calculate the critical values of each selected crop; 3. Develop an LSTM system that provides analyses according to the current soil conditions and weather forecast information; the system will reveal the conditions of the soil, and water the land to balance the condition and reach an optimal status if the soil pH is too high. The research is capable of enhancing crop yields and optimizing the land.

如今，农业行业一直在积极开发智能化和自动化技术，以减少劳动力并提高产量。过去，农民通常遵循经验法则来种植农作物。但是，由于剧烈的气候变化，农民仅凭经验法则就难以应对，这会导致农作物受损。因此，输入科学的数据开发和技术对优化农作物的环境参数并进一步提高产量至关重要。另外，许多农场需要传播农药以避免病虫害；但是，过多的农药可能会导致土壤碱化。为了丰富土地的增长能力，农民将对土地施肥；但是，太多的话也会引起土壤酸化，这将需要离开土地休耕地以改善土壤质量。该研究提供了基于LSTM的智能农业系统。该系统开发了一个物联网（IoT）来监视土壤，阳光和温度的环境条件；此外，该研究还结合了中央气象局提供的信息，以预测浇水的时间，并通知农民有关建议的农药和化肥的使用量。本文的特点如下：1．根据适应性建立农作物的聚类树； 2。2.计算每种选定作物的临界值；3.开发一个LSTM系统，根据当前土壤状况和天气预报信息进行分析；系统会显示土壤状况，如果土壤的pH值过高，可以给土地浇水以平衡条件并达到最佳状态。该研究能够提高农作物的产量并优化土地。