IOT Technology for Fertilizer Recommendation using Naive Bayes Classification to Increase Coconut Yield

Fertilizer recommendation to most agricultural crops is based on response curves. Such curves are constructed from field experimental data, obtained for a particular condition and may not be reliable to be applied to other regions. Fertilizer Recommendation System for Coconut Crop based on the water consistency will provide a more coconut yield. This paper is fully focused on coconut yield using data analytics method. The System considers the expected productivity and plant nutrient use efficiency to estimate nutrient demand, and effective rooting layer, soil nutrient availability, as well as any other nutrient input to estimate the nutrient supply. For producing more coconut, we propose a naive bayes algorithm to analyse the activity of the coconut to produce more quantity. The data set for the development of the System for coconut trees was obtained from IOT based dataset. Dataset were collected and generate the result to produce the high yield of coconut. We also prove the accuracy level for analysing the coconut and minimize the time level.