Smart Farming Assistant for Sustainable Farming

Precision Farming emerges as a way to tackle the practices that deplete the soil of its nutrients and provide ways in sustainable ways to cultivate and replenish the soil naturally. The advancements in technologies like IOT, Data analysis techniques and learning methodologies, led to the finding of fascinating patterns. The extraction of information from datasets such as crop recommendation, Pest and Weed by applying pre-trained algorithms like MobileNet (98%) and Inception (97%) have delivered precise results compared to other models. These findings enable precision farming, where farmers will be able to obtain precise results and guidance according to their farming conditions. The global precision farming market size is estimated to rise from $ 10.43 billion in 2024 to $ 27.29 billion by 2035, growing at a CAGR of 9.1%, during the prognostic period. By utilizing datasets and the use of ML & DL models aided us to develop an easily understandable and informative application. Additionally, the use of Generative AI (Gemini) further refines the model’s accuracy, guaranteeing solutions that are well-suited to the targeted audience. Our research aims to provide factual and insightful information from the collected sources and optimize agricultural productivity and resource management.