In this paper, among the W-S-R relationship methods proposed by Lee, et. al., (2020) to produce rain-based rain information in real time, we tried to produce actual rain information by applying machine learning techniques to take into account the effects of wiper operation. To this end, rain sensor proposed the Graded Descent and Threshold Map method for pre-processing the cumulative value of the difference before and after wiper operation by utilizing four sensitive channels for optical sensors developed by Kim Byung-sik (2016) and using rain sensor data produced by five rain conditions in indoor artificial rainfall experiments. This method is the method of producing rainfall information by calculating the average value of the Threshold according to the rainfall conditions and channels, creating a Threshold Map corresponding to the grid 4 (channel) x 5 (thinking of rainfall information) and applying Optima Rainfall Intensity among the big data processing techniques. For the verification of these proposed findings, the application was evaluated by comparing the rainfall observations with the methods presented by Lee, et. al., (2020).

Abstract
1. 서 론
2. 연구방법
    2.1. 레인센서를 이용한 실내실험
    2.2. 머신러닝 기법을 이용한 레인센서 자료 전처리
3. 적용 및 결과
    3.1. Gradient Descent 알고리즘 적용
    3.2. 실외 강우 관측을 통한 W-S-R 관계식 검증
4. 결론 및 고찰
REFERENCES

• 이병현(강원대학교 방재전문대학원) | Byung-Hyun Lee (Department of Urban and Environmental and Disaster Management, Graduate School of Disaster Prevention, Kangwon National University)
• 김병식(강원대학교 방재전문대학원) | Byung-Sik Kim (Department of Urban and Environmental and Disaster Management, Graduate School of Disaster Prevention, Kangwon National University)
• 이영미((주)에코브레인) | Young-Mi Lee (ECOBRAIN Co. Ltd.)
• 오청현(강원대학교 방재전문대학원) | Cheong-Hyeon Oh (Department of Urban and Environmental and Disaster Management, Graduate School of Disaster Prevention, Kangwon National University)
• 전원혁(강원대학교 방재전문대학원) | Weon-Hyouk Jun (Department of Urban and Environmental and Disaster Management, Graduate School of Disaster Prevention, Kangwon National University) Corresponding author
• 최정렬(강원대학교 방재전문대학원) | Jung-Ryel Choi (Department of Urban and Environmental and Disaster Management, Graduate School of Disaster Prevention, Kangwon National University)