Implementing AI on low-power embedded devices for digital water meter identification and data transfer via lora network

https://doi.org/10.31130/ud-jst.2024.173ICT
Tóm tắt: 18 | PDF: 21

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Author

  • Thai Vu Hien
    The University of Danang - University of Science and Technology, Vietnam

Từ khóa:

LoRa
Machine Learning
Water Meter
Image Processing
Low Power

Tóm tắt

This study introduces an artificial intelligence system implemented on the ESP32-CAM platform, aimed at conducting optical character recognition (OCR) on water meters. Leveraging LoRa technology for data transmission ensures efficient energy utilization and convenient long-range communication capabilities. The system achieves an impressive accuracy rate of 98.2% in identifying water meter readings, showcasing its reliability. Proposed as a feasible solution, it offers the advantages of low energy consumption, cost-effectiveness, and flexibility in widespread deployment, particularly leveraging existing water meter infrastructure. Thus, this research presents a promising choice for various applications beyond merely reading water meter readings. Its efficient and accurate OCR functionality makes it suitable for diverse scenarios, ranging from smart city initiatives to industrial automation processes. With its ability to integrate seamlessly into existing infrastructure and deliver reliable results, this system stands poised to revolutionize OCR applications in various domains, contributing to enhanced efficiency and productivity.

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Jun 30, 2024
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Cách trích dẫn
Hien, T. V. “Implementing AI on Low-Power Embedded Devices for Digital Water Meter Identification and Data Transfer via Lora Network”. Tạp Chí Khoa học Và Công nghệ - Đại học Đà Nẵng, vol 22, số p.h 6A, Tháng Sáu 2024, tr 46-51, doi:10.31130/ud-jst.2024.173ICT.

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