Precision agriculture (PA) relies heavily on an accurate and efficient approach to determine soil properties. High resolution data of soil parameters are collected by placing various sensors in contact with or close to soil and crops to enable dynamic mapping of soil variability across agricultural fields. The combination of spectral, electrical, and mechanical sensing methods improves the resolution and reliability of soil assessments. The proximal sensing greatly improves decision-making in variable rate fertilization, irrigation scheduling, and land preparation. This work investigates the use of proximal sensing technologies to analyze soil characteristics, such as texture, moisture, nutrient levels, and organic matter. This approach allows for precision farming techniques and more efficient use of organic fertilizers. This innovation has the potential to fundamentally change land management practices among farmers. The suggested model is simple to use and reasonably lower priced. This strategy reduces input waste and environmental impact while simultaneously increasing productivity and encouraging sustainable farming methods.