제주대학교 Repository

머신러닝을 활용한 IoT 작물재배시스템 내부온도 예측에 관한 연구

Metadata Downloads
Abstract
This study focuses on efficient production, away from research that focused on automating cultivation facilities and increasing convenience. In this study, we discuss a model that predicts the internal temperature of the IoT crop cultivation system using machine learning, which derives the internal temperature prediction model of the crop cultivation system and ensures crop growth under optimal environmental conditions.
In this study, weather data were collected through external temperature data, internal temperature data, controller temperature data measured in crop farming systems and Agricultural Weather Information Service API before deriving the optimal prediction model. Afterwards, the collected data was refined to the appropriate form for the analysis. And preprocess of the data was carried out with process of parsing the information needed for the analysis and missing value. One of the learning methods of machine learning, Supervisited Learning, is used to predict optimal internal temperatures by utilizing pre-processing data, and multi-layer perceptron algorithm is utilized as a neural network model to efficiently derive predictive models. In addition, two predictive models were classified according to the input variables. The effect of cultivation materials on the system, which is one of factors that affect internal temperatures data, is Formulated. And by comparing the results of predictive models that applied this formula with those of predictive models that did not apply the expression, we derive a model that predicts patterns similar to the temperature within the real system.
Author(s)
허수미
Issued Date
2021
Awarded Date
2021. 2
Type
Dissertation
URI
https://oak.jejunu.ac.kr/handle/2020.oak/23530
Department
대학원 메카트로닉스공학과
Advisor
강철웅
Table Of Contents
제 1 장 서론 1
1. 연구 배경 및 필요성 1
2. 연구 목적과 방법 2
제 2 장 환경데이터 수집 및 전처리 4
1. 환경제어시스템 외형설계 4
2. 환경제어시스템 컨트롤러 설계 6
3. 환경제어시스템 통신프로토콜 설계 7
4. 모델 도출을 위한 데이터 수집 8
5. 모델 도출을 위한 데이터 처리 10
제 3 장 환경데이터 예측모델 도출 13
1. 예측모델 설정 13
2. 예측모델 도출방법 14
3. 예측 Model A 도출 15
4. 예측 Model B 도출 22
제 4 장 연구결과 32
1. 재배함 재질 영향 식 유무에 따른 모델 예측결과 비교 32
2. 재배함 재질 영향 식 유무에 따른 모델 성능평가 결과 비교 34
제 5 장 결론 40
참고문헌 42
Degree
Master
Publisher
제주대학교 일반대학원
Citation
허수미. (2021). 머신러닝을 활용한 IoT 작물재배시스템 내부온도 예측에 관한 연구
Appears in Collections:
Faculty of Applied Energy System > Mechatronics Engineering
Authorize & License
  • AuthorizeOpen
Files in This Item:

Items in Repository are protected by copyright, with all rights reserved, unless otherwise indicated.