A novel sensor network is developed for the detection of necessary parameters related with environmental condition which has direct influence on the growth rate of potato plant. The embedded system is efficient enough to determine the real-time condition of soil in terms of pH, water content of the soil at runtime in ppm unit, NPK (Nitrogen-Phosphorous-Potassium content), TDS (Total Dissolved Solid); and atmospheric status including temperature, humidity, and intensity of Sun. Periodical growth monitoring is performed using load cell, which reflects the health condition of the plant under supervision with time. Supervised learning algorithm is invoked for analyzing the data obtained using the hardware set-up for decision making, based on the pre-processing of data obtained from well-known database. The entire set-up is extremely beneficial for farmers for real-time assessment of agricultural condition, which is directly correlated with plant growth.