Crop Monitoring System Using IOT

Abstract

Currently, the low agricultural output is causing farmers to suffer. Low crop growth is primarily caused by knowledge of soil fertility and crop selection, even though proper crop selection is the primary booster key for enhancing agricultural yield by doing soil analysis and taking metrological elements into consideration. Farmers with limited experience in conventional farming are finding it difficult to make wise crop selection choices in the current environment. The low soil fertility is caused by the same crop being chosen for each seasonal cycle. The goal of this research is to use IoT devices to create an accurate and efficient system. Compared to the outdated manual laboratory testing procedures, which are subject to human errors, such a system is predictable. A crop's proper selection is mostly important in the agricultural field. As a contribution, we offer Smart Crop Selection (SCS), an IOT-based approach that is based on soil and metrological factor data. These variables include soil moisture content, temperature, and precipitation. Because these issues are not given as much care as they should, existing IoT-based systems are less efficient than our proposed model. Real-time sensory data is transmitted to Firebase cloud for analysis in the suggested model