India's passenger traffic primarily relies on the road network for commuting. As a result, the demand for transport infrastructure has led to rapid growth in road construction across the country. California Bearing Ratio (CBR) tests measure strength of subgrade soil, which is essential for pavement design. In practice, the CBR value is often estimated through index and strength properties of soil, since it is easier as compared to the conventional time-consuming laboratory CBR testing. Over the years, a lot of efforts has been taken for developing CBR from index and strength properties correlation equations, most of which are based on regression analysis. Moreover, most of the correlation equations developed are based on a wide dataset compiled from different regions, which makes them incapable of accounting for the spatial variability of soil. This study presents a quick approach to estimate onsite CBR values using sensor acceleration data, avoiding time-consuming laboratory tests. An Arduino Uno sensor collected data for 19 locations in Dhule district, Maharashtra was used in present study. The developed CBR equations using sensor data showed a strong correlation with conventional regression equations and experimental results.