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Drive Health: Road Condition Detection

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Roadways play an essential role in today’s society by contributing to economic growth and development, providing access to all members of society and fast routes to travel on efficiently. With increased numbers of vehicles on the roads, the quality of the roads is deteriorating at a faster rate than can be maintained and repaired. This decrease in road health materializes as hazards such as potholes that can cause significant damage to vehicles on the road. Currently, roads’ health is monitored manually and thus done infrequently due to it being both time-consuming and costly for the responsible local transit authorities. Therefore, many road quality issues are repeatedly reported by the people who drive on them before any inspection or repair efforts are undertaken by the transit authorities. This manual process of reporting potholes and other road hazards is an inefficient process requiring filling out forms or making phone calls while remembering the exact location of the pothole or road hazard.

This chapter presents Drive Health, an Internet of Things (IoT) system developed to crowdsource the monitoring of the health of roadways by informing transit authorities of pothole locations. Drive Health includes a smart sensor and performs machine learning on accelerometer data to process and analyze the data without using the cloud. If the system determines that the data indicates the existence of a pothole, the location of where the data was collected is recorded and sent to a web server which can then be automatically shared with the transit authorities responsible for that road location.


  • Pothole detection
  • Internet of Thing (IoT)
  • Accelerometer
  • Global Positioning System (GPS)
  • Machine Learning (ML)

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  • DOI: 10.1007/978-3-030-92968-8_9
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Many thanks are due to Santa Clara University’s School of Engineering for their financial support of the project through their undergraduate senior design project funding, as well as to SCU’s IoT (SIoT) Lab, the Frugal Innovation Hub (FIH), and the Ethical, Pragmatic, and Intelligent Computing (EPIC) Research Laboratory for their continued support of Drive Health.

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Correspondence to Navid Shaghaghi .

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Ferguson, P., Walker, B., Shaghaghi, N., Dezfouli, B. (2023). Drive Health: Road Condition Detection. In: Cagáňová, D., Horňáková, N. (eds) Industry 4.0 Challenges in Smart Cities. EAI/Springer Innovations in Communication and Computing. Springer, Cham.

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