Abstract:
CROP RECOMMENDATION SYSTEM, driven by the integration of IoT and machine
learning, has the potential to revolutionize traditional farming practices by providing farmers
with real-time, actionable information to make informed decisions. One of the key applications
of this technology in crop recommendation, where the right crop to grow in a specific location
can be determined through the analysis of environmental data such as soil ph, temperature,
humidity, rainfall, and soil nutrients such as nitrogen, phosphorus, and potassium. The IoT
system collects data from various sensors and weather stations, which is then processed using
machine learning algorithms to determine the best crops to grow in a specific location. This
analysis takes into account historical weather patterns, soil characteristics, and other relevant
data, providing farmers with an up-to-date understanding of the optimal growing conditions
for different crops. With this information, farmers can make informed decisions about what to
plant, when to plant, and how to optimize yields. Smart crop recommendation not only helps
farmers improve their yields, but it also has the potential to address the global food crisis. By
optimizing crop selection, farmers can grow more food on less land, reducing the need for
deforestation and other environmentally harmful practices
