农业工程:基于物联网和图像处理的农业监测与推荐系统

N. G. Croos, Sophinia R, Afkar Ahamedh, Dirushan J., U. Rajapaksha, Buddika Harshanath
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引用次数: 1

摘要

农业是支持斯里兰卡经济的主要部门。在农业实践中引进新技术将对农民有很大帮助。土壤的pH值和水分含量在监测土壤肥力、灌溉水平和植物生长方面起着至关重要的作用。有时农民不能根据土壤条件、种植季节和地理位置选择合适的作物种植。土壤肥力是农业中决定土壤质量的一个重要方面。土壤养分在每次收获后都会耗尽,必须加以补充。灌溉系统需要控制洪水水位,适应水稻的发展。在从生长到收获的整个周期中,水对土地的准备、作物的种植和作物的维持都是必需的。水稻病害的发生和害虫的存在是影响水稻生产和品质的两个关键因素。该行业最大的问题之一是缺乏一种可靠的方法来确定水田土壤的营养水平,确定合适的作物,了解灌溉水平,并确定害虫。这导致农民结束自己的生命,离开农业,搬到城市地区寻找工作。本研究提出了一个系统,通过考虑所有相关因素,如土壤养分水平、土壤肥力、水分水平、PH值、温度和害虫图像,帮助农民进行作物选择、肥料推荐、灌溉和害虫检测。移动应用程序和智能方法可以适应每个领域的作物需求,可以为农民提供有关合适作物、土壤肥力、合适肥料、灌溉水平和识别害虫的信息,从而提高作物产量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Agro-Engineering: IoT and Image processing based agriculture monitoring and recommendation system
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.
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