Advanced Industrial SCIence (산업과 과학)

Convergence Society for SMB (중소기업융합학회)
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A Real-Time Drinking Water Quality Monitoring Model based on IoT Cloud Platform

IoT 클라우드 플랫폼 기반 실시간 식수 수질 모니터링 모델

  • Chai Ting (Dept. of Computer and Media Engineering, Tongmyong University) ;
  • Jun-Yeon Lee (Dept. of Digital Contents, Tongmyong University)
  • 시정 (동명대학교 컴퓨터미디어공학과 ) ;
  • 이준연 (동명대학교 디지털콘텐츠학과)
  • Received : 2025.04.20
  • Accepted : 2025.05.20
  • Published : 2025.05.30
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Abstract

Water quality safety is increasingly threatened by industrial pollution and resource scarcity, and traditional monitoring approaches are often inefficient and slow to respond, leading to delayed contamination alerts. In this paper, we propose a real-time drinking water quality monitoring system based on an IoT cloud platform. The proposed technology adopts a multi-layer architecture integrating low-power communication, edge computing, and Docker containerization while employing machine learning algorithms such as Random Forest and Gradient Boosting for feature extraction, data cleaning, and predictive modeling. Experimental results indicate that the RF model achieves an accuracy of 96.0% with only 1.7 seconds of latency, effectively reducing undetected contamination risks while providing broad coverage at reduced costs. Future work will explore unknown contaminant detection, blockchain-based data security, and solar-powered operation for sustainable deployment.

산업 오염과 자원 부족으로 인해 수질 안전이 점점 더 위협받고 있으며, 기존의 모니터링 방식은 비효율적이고 대응 속도가 느려 오염 경보가 지연되는 경우가 많다. 본 논문에서는 IoT 클라우드 플랫폼을 기반으로 한 실시간 식수 수질 모니터링 시스템을 제안한다. 제안 기술은 저전력 통신, 엣지 컴퓨팅, 도커 컨테이너화를 통합한 다계층 아키텍처를 채택하고 특징 추출, 데이터 정리, 예측 모델링을 위해 랜덤 포레스트와 그라데이션 부스팅과 같은 머신러닝 알고리즘을 사용한다. 성능 평가 결과, RF 모델은 1.7초의 지연 시간으로 96.0%의 정확도를 달성하여 미탐지 오염 위험을 효과적으로 줄이면서 저렴한 비용으로 광범위한 커버리지를 제공한다. 또한 알려지지 않은 오염 물질 탐지, 블록체인 기반 데이터 보안, 지속 가능한 배포를 위한 태양광 발전 운영 등에 활용 될 수 있다.

Keywords

Acknowledgement

This work was supported by Tongmyong University Research Grant of 2024(2024A022)

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