Harnessing AI Technologies for Sustainable Agricultural Practices: Innovations in Soil Analysis and Crop Management
DOI:
https://doi.org/10.5530/bems.12.1.5Keywords:
Autonomous, Forecasting, Machine Learning, Patterns, Productivity, SustainabilityAbstract
Challenges in agriculture sector are becoming significant a rapidly growing population and declining agricultural productivity. Despite the rigorous efforts of the farmers to cultivate crops, they encounter numerous obstacles stemming from insufficient knowledge about soil characteristics across the demographics of the farmers stacked with uncertain and fluctuating weather patterns. This research highlights the use of Machine Learning (ML) and Computer Vision (CV) to simplify and automate the process with higher yields. Moreover, this study also touches the inclusion of Unmanned Aerial Vehicles (UAVs) to drastically reduce the intense physical work with technology and bring out advancement in agriculture. With the live status update across soil-understanding and nourishment - and soil parameters, forecasting weather features-sunlight rain, wind, etc. Farmers can optimize the crop growth with optimized decision-making and promoting sustainability.
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