Soil mapping for farming productivity: internet of things (IoT) based sustainable agriculture

The primary objective of this research is to employ predictive models for determining soil nutrients and various other soil variables, thereby enabling the selection of appropriate crops and recommending suitable fertilizers for agricultural land in Vellore district. The ultimate goal is to facilitate informed decision-making within the data analytic system, addressing soil nutrient deficiencies, fertilizer utilization, and crop selection. The study demonstrates that IoT-based data processing techniques play a crucial role in accurately predicting the optimal crops for specific fields and suggesting the appropriate fertilizer dosage for each crop. The soil analysis in Vellore district revealed that it naturally contains approximately 60