International Journal of Science, Engineering and TechnologyAuthors: Nitish Sharma, Dr Komal Garg
Abstract: The requirement for appropriate agricultural care practices and the increase in water worries are significant challenges that require the highest level of propriety. In light of these considerations, the current work has developed an intelligent agricultural irrigation system. Designing a decision-support system based on an embedded system with machine learning integrated is the current approach. To make accurate decisions in an irrigation management plan, an LSTM model that learns from a crop recommendation dataset has been created. However, an Adriano Uno-based embedded system has been created in order to evaluate the LSTM model's choice. According to the experiment's findings, the LSTM model was trained to make decisions with a promising accuracy
DOI: https://doi.org/10.5281/zenodo.16811610
