A healthy road network plays a significant role in the socio-economic development of any country. Road management authorities struggle with pavement repair approaches and the finances to keep the existing road network to its best functionality. It has been observed that real-time road condition monitoring can drastically reduce road and vehicle maintenance expenses. There are various methods to analyze road health, but most are either expensive, costly, time-consuming, labor-intensive, or imprecise. This study aims to design a low-cost smart road health monitoring system to identify the road section for maintenance. An automized sensor-based system is developed to assist the road sections for repair and rehabilitation. The proposed system is mounted in a vehicle and the data have been collected for a more than 1000 km road network. The data have been processed using SPSS, and it shows that the proposed system is adequate for detecting the road quality. It is concluded that the proposed system can identify the vulnerable sections to add to the pavement maintenance plan. In the future, the created application can be launched as a smart citizen app where each car driver can install this application and can monitor the road quality automatically.