• Shital Tanaji Nagane
• Dr.P.D.Lambate

Ingenious, frugal, and cost-effective irrigation techniques have developed to meet the world's population's need for sweet water. Put differently, one should use water sparingly enough to preserve the limited supply of sweet water. The majority of the water was squandered as a result of poor irrigation techniques. We used a clever strategy that is expertly capable of employing ontology to make half of the decisions; the remaining half is based on the values of the sensor data. The final decision, which is the outcome of a machine learning algorithm, is derived from the choice made by the ontology and the sensor values taken together (KNN). Additionally, a new edge server is placed in between the GSM module and the primary IoT server. This approach will lower the delay rate in addition to preventing the IoT server from being overworked when processing data. In order to predict the amount of water required for a field of crops, this method links the Internet of Things with a network of sensors. It then uses an Android application edge to display the results. The data is cleverly traced, analyzed, and only a portion is transferred to the main IoT server.

Smart Irrigation, Water Harvesting, C4.5, KNN, IOT System

"Smart Irrigation System ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 4, page no.h750-h755, April-2024, Available :http://www.jetir.org/papers/JETIR2404786.pdf

"Smart Irrigation System ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 4, page no. pph750-h755, April-2024, Available at : http://www.jetir.org/papers/JETIR2404786.pdf