Automated Wireless Crack Detection System for Structural Health Monitoring Using Artificial Intelligence and Raspberry Pi

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@article{1718516,
      author = {Uday Wagh, Yash Waskar, Tushar Gaikwad, Prof. Ajinkya Shah},
      title = {Automated Wireless Crack Detection System for Structural Health Monitoring Using Artificial Intelligence and Raspberry Pi},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {9},
      number = {11},
      pages = {4938-4942},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1718516.pdf},
      abstract = {Modern infrastructures including buildings, dams and industrial facilities are expected to function safely for extended periods of time despite being subjected to material deterioration, dynamic loads and natural deterioration. The conventional method of inspection relies on periodic manual inspection, which is often inadequate for early detection of structural degradation. Structural Health Monitoring (SHM) has been proposed as an intelligent approach for the continuous evaluation of structures using sensing technology. The development of wireless sensor networks has greatly reduced the complexity and cost of implementation, thereby providing an effective SHM approach. The research aims to explore the possibility of developing a low-cost smart wireless SHM approach using raspberry pi sensor sensors and wireless communication using microcontroller technology. The methodology of the proposed approach is based on ultrasonic distance measurement for the detection of structural deformation, displacement, and crack growth using non-contact sensing technology, and wireless data acquisition for data transmission.},
      keywords = {Crack Detection, Infrastructure Monitoring, Raspberry pi sensor, Smart Sensors, Structural Health Monitoring.},
      month = {May},
      doi = {https://doi.org/10.64388/IREV9I11-1718516}
  }