Agro-Engineering: IoT and Image processing based agriculture monitoring and recommendation system

N. Godfrri Croos, Sophinia R, Afkar Ahamedh, Dirushan J.,U.U.Samantha Rajapaksha,Buddika Harshanath

2022 6th International Conference on Electronics, Communication and Aerospace Technology(2022)

引用 1|浏览0
暂无评分
摘要
Agriculture is the primary sector that supports Sri Lanka's economy. The introduction of novel technologies into agricultural practices will be of great assistance to farmers. The soil's pH and moisture content play a crucial part in the monitoring of soil fertility, irrigation level, and plant growth. Sometimes farmers were unsuccessful in selecting the appropriate crops to grow based on the conditions of the soil, the planting season, and the geographic location. Soil fertility is an important aspect in agriculture to determine the soil's quality. Soil nutrients are depleted after each harvest and must be replenished. The Irrigation system needs to control flood levels and adapt to paddy development. Water is necessary for the preparation of the ground, the planting of the crop, and crop upkeep throughout the growing-to-harvest cycle. The occurrence of paddy plant diseases and the presence of pests are two key factors that influence the production and quality of rice. One of the industry's biggest problems is the lack of a reliable method for determining paddy field soil nutrient levels, identifying the suitable crop, knowing the level of irrigation, and identifying the pest. This leads to farmers taking their own lives, leaving the agricultural industry, and moving to urban areas in search of work. This research has proposed a system to assist farmers in crop selection, fertilizer recommendation, irrigation, and pest detection by taking into account all of the relevant factors such as soil nutrient level, soil fertility, moisture level, PH, Temperature, and pest images. A mobile application and an intelligent method that is adapted to the requirements of the crop in each field can provide the farmer with information about the suitable crop, fertility of the soil, suitable fertilizer, irrigation level, and identified pest which will increase crop yield.
更多
查看译文
关键词
Machine learning,Deep learning,Internet of things(IoT),Soil monitoring,Fertilizer recommendation,Irrigation system,Pest detection
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要