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빅데이터 기반 인공지능 동파위험 정보서비스 개발을 위한 연구

A Study on the development of big data-based AI water meter freeze and burst risk information service

  • Lee, Jinuk (Department of Civil Engineering, Chungnam National University) ;
  • Kim, Sunghoon (AI Research Center, K-water) ;
  • Lee, Minjae (Department of Civil Engineering, Chungnam National University)
  • 투고 : 2023.01.12
  • 심사 : 2023.04.19
  • 발행 : 2023.05.31

초록

겨울철 동파는 물사용 불가, 2차 피해 및 계량기 교체비용 발생 등 많은 사회적 비용을 발생시키고 있다. 정부에서는 지방상수도 시설의 현대화를 위해 많은 노력을 기울이고 있으며, 특히나 전국적으로 SWM 사업을 추진 중에 있다. 본 연구에서는 수용가의 최접점에 설치되는 스마트 미터링에 착안하여 기존의 대기온도가 아닌 계량기 함내 온도를 기반으로 하는 새로운 동파위험 알림 정보서비스를 계획하였다. 또한 본 연구에서는 전국적으로 설치된 스마트미터의 수량적인 한계를 극복하기 위하여, 온도센서로부터 취득된 자료들을 바탕으로 물리적인 온도센서가 없는 지역의 온도를 예측하는 인공지능 기반의 온도예측 모델을 개발하였고, 최적화 과정을 통해 전국을 대상으로 하는 수도계량기 동파위험 정보서비스(안)을 구상하였다.

Freeze and burst water meter in winter causes many social costs, such as meter replacement cost, inability of water use, and secondary damage by freezing water. The government is making efforts to modernize local waterworks, and in particular, is promoting SWM(Smart Water Management) project nationwide. In this study suggests a new freeze risk notification information service based on the temperature by IoT sensor inside the water meter box rather than outside temperature. In addition, in order to overcome the quantitative and regional limitation of IoT temperature sensors installed nationwide, and AI based temperature prediction model was developed that predicts the temperature inside water meter boxes based on data acquired from IoT temperature sensors and other information. Through the prediction model optimization process, a nationwide water meter freezing risk information service was convinced.

키워드

과제정보

본 연구는 국가수도정보센터의 국가상수도정보시스템 고도화 관련, K-water AI연구센터의 지원과 시스템 기능개선용역성과의 일부를 활용하였으며, 한국연구재단 이공분야기초연구(NRF-2022 R1I1A3068942)에 의한 일부 연구비 지원에 감사드립니다.

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