Key Features:

• The data gathered from IoT devices allowed us to gain insight into soil nutrient levels, temperature changes throughout the atmosphere and seasonally based on a variety of factors such as rainfall rates.
• This information was then used for further analysis in order determine when best times were amid different types or environments so that optimal growing conditions could be achieved without compromising any other variables like solar radiation exposure.
• The data gathered from sensors was passed to a principal component analysis (PCA), which reduced features in order extract more accurate predictions.
• Machine Learning algorithms such as Linear Regression and Decision Trees were also implemented for forecasting using past information about soil nutrient levels & other parameters.