Multi-Sensor System for Underwater Pothole Detection to Enhance Road Safety During Monsoon Seasons

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This is an unedited manuscript accepted for publication and provided as an Article in Press for early access at the author’s request. The article will undergo copyediting, typesetting, and galley proof review before final publication. Please be aware that errors may be identified during production that could affect the content. All legal disclaimers of the journal apply.

Year : 2026 | Volume : 4 | 01 | Page :
    By

    Jashanpreet Singh,

  • Gaurav,

  • Harshit,

  • Jacob Chacko,

  1. Student, Department of Electronics and Communication Engineering, CEC-CGC Landran, Punjab, India
  2. Student, Department of Electronics and Communication Engineering, CEC-CGC Landran, Punjab, India
  3. Student, Department of Electronics and Communication Engineering, CEC-CGC Landran, Punjab, India
  4. Student, Department of Electronics and Communication Engineering, CEC-CGC Landran, Punjab, India

Abstract

Monsoon seasons across India and similar tropical regions severely compromise road safety by causing water accumulation that conceals dangerous potholes beneath stagnant pools, leading to frequent vehicle damage, tire punctures, and fatal accidents. Traditional detection methods relying on smartphone accelerometers, ultrasonic sensors, or machine vision fail under flooded conditions due to acoustic signal reflection at water surfaces and optical distortions from glare and turbidity. This research proposes an innovative multi-sensor fusion system that integrates a low-cost HC-SR04 ultrasonic sensor for dry pothole detection with a 405 nm blue laser diode structured-light module for underwater pothole profiling, enabling comprehensive road hazard identification regardless of surface wetness. The ultrasonic sensor continuously measures road-to-sensor distance via time-of-flight, flagging sudden depth variations exceeding 3 cm as dry potholes. Complementarily, the blue laser projects a thin line pattern across the road surface, which a co-aligned CMOS camera captures to reveal submerged topography through laser line deformation analysis. Custom image processing algorithms—employing grayscale conversion, Gaussian noise filtering, Sobel edge detection, and Hough transform line fitting—extract pothole depth and width from the distorted laser profile using calibrated camera-laser triangulation geometry. An Arduino Uno microcontroller orchestrates real-time sensor polling, preliminary decision logic (Boolean OR fusion of ultrasonic and optical flags), debounce filtering, and driver alerts via multi-color LEDs and variable-tone buzzer. Theoretical simulations based on sensor datasheets and optical propagation models predict >90% detection accuracy for potholes 3-15 cm deep in water depths up to 10 cm, with end-to-end latency under 200 ms suitable for vehicular applications. Total prototype cost remains below ₹7000, making deployment feasible across budget-constrained municipalities. This embedded solution bridges critical gaps in existing technologies and establishes a scalable foundation for monsoon-resilient intelligent transportation systems in developing regions.

Keywords: Underwater pothole detection, sensor fusion, blue laser structured light, ultrasonic ranging, embedded real-time processing, monsoon road safety, Arduino microcontroller, image processing algorithms.

How to cite this article:
Jashanpreet Singh, Gaurav, Harshit, Jacob Chacko. Multi-Sensor System for Underwater Pothole Detection to Enhance Road Safety During Monsoon Seasons. International Journal of Mechanical Dynamics and Systems Analysis. 2026; 04(01):-.
How to cite this URL:
Jashanpreet Singh, Gaurav, Harshit, Jacob Chacko. Multi-Sensor System for Underwater Pothole Detection to Enhance Road Safety During Monsoon Seasons. International Journal of Mechanical Dynamics and Systems Analysis. 2026; 04(01):-. Available from: https://journals.stmjournals.com/ijmdsa/article=2026/view=246937


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Ahead of Print Subscription Original Research
Volume 04
01
Received 16/01/2026
Accepted 10/03/2026
Published 26/03/2026
Publication Time 69 Days
2

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