Smart agriculture irrigation system using integrated system using IOT and ML

In recent years, precision agriculture has attracted a lot of interest as a result of the increasing global population's need for food and water. Therefore, farmers will require To accommodate this demand, there must be enough water and land suitable for agriculture. Because of the restricted Because both resources are available, farmers require a solution that alters how they conduct themselves. The key to effective irrigation is a method to produce higher, better, and more lucrative yield without as much resources. a number of machine learning-based In order to use more water, irrigation models have been proposed. efficiently. Due of these models' low capacity for learning, Unpredictable climates are not ideal for them.This technology, which incorporates feedback, maintains its performance better in any region's weather for any length of time. DL forecasts the cubic content of soil moisture for the coming day, the duration of the watering, and the geographic heterogeneity of water required to irrigated the farms using a LTSM. The simulation findings show that DLiSA uses water more wisely than cutting-edge technologies. models in the region used for experimental farming.