The soil nutrients in a certain agricultural region are chosen to optimize the possibility of high crop yields. Local farmers have raised concerns about the prevalence of common heavy metals, including lead, mercury, arsenic, and cadmium, in soil sediments. These concerns are particularly focused on areas near polluted bodies of water. These are laboratory techniques used to reduce the amount of heavy metals in soil and to create the right amount of nutrients by applying appropriate fertilizers. The issues can be resolved by doing a comprehensive soil analysis. The main goal of this project is to create a versatile Internet of Things (IoT) device that uses Raspberry Pi and NIR spectroscopy for soil analysis. This device aims to reduce the need for farmers to perform time-consuming laboratory soil testing and to offer cost-effective soil analysis. The device was operated using an Arduino MEGA 2560 connected to a TCD1304AP. By setting up the Internet of Things (IoT) on Raspberry Pi using Django and pgAdmin, any user connected to the specified WiFi network can access a webpage that shows different outcomes. The results encompass data regarding the composition of the soil, its pH level, suggested crops, and potential remedies and treatments for the soil. The data analysis demonstrated a precision of 95% in determining the quantities of macronutrients in the soil. The proposed system exhibited a 25.56% margin of error and a 28.57% disparity in pollutant concentrations.