Identification of Environmental Factors in Fruit Disease by Logistic Regression

Vasanth Ragu,이명배,이명훈,A.B.M. Salman Rahman,박장우,조용윤,신창선 한국지식정보기술학회 2018 한국지식정보기술학회 논문지 Vol.13 No.5

Plant diseases are one of the most significance issues in agriculture fields. The diseases destroy fruits and are decreased the production rate. They also decrease the economic growth in worldwide and increase the demand about preventing plant diseases. The major cause of plant diseases is climate changes, weather conditions and environmental factors. To prevent the diseases, we need to identify the plant diseases about corresponding environmental factors. In this study, we analysis the plum data and identify the plant diseases with corresponding environmental factors by using Logistic Regression model. The first process is to identify the number of diseases and its type, and then implement Logistic Regression to predict the diseases by using environmental factors as inputs. Finally, we compare the actual value of diseases with predicted value of diseases, and need to check the accuracy of diseases by using correlation method. We also find the environmental factors for the reasons to forms more diseases. In result and discussion, it would be clearly explained about the plum diseases and their environmental factors.

스마트 전력 기기의 온도 분석에 관한 연구

( Ragu Vasanth ),이명배 ( Myeongbae Lee ),김영현 ( Younghyun Kim ),박명혜 ( Myunghye Park ),이승배 ( Seungbae Lee ),박장우 ( Jwangwoo Park ),조용윤 ( Yongyun Cho ),신창선 ( Changsun Shin ) 한국정보처리학회 2017 정보처리학회논문지. 컴퓨터 및 통신시스템 Vol.6 No.8

전신주와 같은 전력 설비에는 스마트한 서비스를 위한 다양한 종류의 센서가 포함되어 있으며, 온도 정보는 전력 설비의 정상 동작 상태를 판단하는 중요한 요소 중 하나이다. 본 연구에서는 칼만 필터(Kalman Filter)와 앙상블 모델(Ensemble Model)을 이용해 스마트 전력 장치의 상태를 판단할 수 있도록 장치의 온도 분석 방법을 제안했다. 제안 된 접근 방식은 서로 다른 위치에 설치된 센서로 부터 수집된 정보 중 온도 데이터를 분류하고 칼만필터 및 앙상블 모델을 사용하여 온도 변화의 특성을 분석했다. 세부적으로 수집된 온도 데이터로부터 기상 온도 데이터와 같은 외부 인자를 제거하고 전력 장치의 각 위치로부터의 실제 장치의 온도값만을 분석했으며, 이 과정에서 칼만필터를 사용하여 오류 데이터를 제거하고 앙상블 모델을 사용하여 매 시간 정상 동작하는 전력 설비의 온도 평균값을 산출했다. 온도 분석에 대한 결과와 논의는 전력 데이터에 분석 결과에 명확하게 설명되어 있다. 마지막으로, 분석된 데이터를 통해 전력 장치가 정확히 동작하는 지를 판단할 수 있는 온도값의 정상범위를 확인하였다. An electrical power utility, like an electrical power pole, includes various kinds of sensors for smart services. Temperature data is considered one of the important factors that can influence the smart operations of this utility. This study suggests a method for temperature data analysis for deciding the status of the smart electrical power utilities by using Kalman Filter and Ensemble Model. The suggested approach separates the temperature data according to the different positions of the temperature sensors of a utility, then uses Kalman Filter and Ensemble Model to analyse the characteristics of the temperature variation. With detailed processes, method explains the variation between an external temperature factor like weather temperature data and the sensed temperature data, and then, analysis the temperature data from each position of electrical power utilities. In this process, the suggested method uses Kalman Filter to remove error data and the ensemble model to find out mean value of every hour of electrical data. The result and discussion of temperature analysis were described clearly with the analysed results of electrical data. Finally, we were able to check the working condition of the power devices and the range of the temperature data foe each devices, which may help to indicate any causalities with respect to the devices in the utility pole.

A Greenhouse Control System Based on Best-Fitted PID Controller to Minimize Energy Cost

Vasanth Ragu,이명배,조용윤,박장우,신창선 한국지식정보기술학회 2018 한국지식정보기술학회 논문지 Vol.13 No.1

In these days, many of greenhouse environments are based on electric devices and ICT technologies. The model suggested in the paper the detailed design of a greenhouse control system adaptability with PID (Proportional Integral and Derivative) controller. Compared with a previous greenhouse control system (GCS), the proposed system is focused on the detailed design of greenhouse control process to minimize energy costs for crop growth in a greenhouse. In the suggested system, there are two important processes namely, Greenhouse Control Process (GCP) and Crop Growth Process (CGP). The two process data, which are crop status information and climate set-point information, are stored in an information storage database. The PID controller works inside the GCP and the environment control decision works inside the CGP. According to the service decision algorithm of it, the controller will work properly in a greenhouse. Using the suggested system with the different combinations such as P, PI, PD and PID, a user can easily simulate energy costs for a greenhouse system and efficiently design the best optimized controller in the greenhouse system. Therefore, the suggested system can provide a feasible solution to reduce or minimize energy cost in the greenhouse and help developments of various applications related with greenhouse environments.

Peak Hour Identification for Traffic Congestion Based on IoT Environments

Vasanth Ragu,Saraswathi Sivamani,이명배,조현욱,조용윤,박장우,신창선 한국지식정보기술학회 2018 한국지식정보기술학회 논문지 Vol.13 No.3

This study deals with the analysis of traffic congestion and the peak hour identification by using Kalman Filter and Ensemble Model. There are different types of traffic congestion, Roadway Traffic congestion, Airways Traffic congestion, Network Traffic congestion, and so on. This study focuses on Roadway Traffic congestion. The peak hour identification is essential to prevent roadway traffic congestion. In roadway traffic congestion, there are two categories in traffic data, namely Roadside Equipment (RSE) data and Video Detection System (VDS) data. Both data were collected from RSE devices and VDS devices, which are located in roadways signals, toll plaza, private sectors, and etc. In traffic data, it may contain error values. So, this paper applies the Kalman Filter for the purpose of removing the error values or inaccurate values and providing the cleaned Traffic data. The suggested study also uses the Ensemble Model to average the traffic data at corresponding hours easily to analyse the traffic data. To identify peak hour, it defines four different models by considering numbers, average times, and average speeds of vehicles. With the suggested method, the perfect peak hour in the traffic data can be easily and exactly obtained. In the tests and results, this paper showed the detailed process of peak hour identification in traffic congestion.

Identification of High Significance Product Items Through the Analysis of Energy Consumption in Steel Factory

A.B.M. Salman Rahman,이명배,Vasanth Ragu,임종현,조용윤,박장우,신창선 한국지식정보기술학회 2019 한국지식정보기술학회 논문지 Vol.14 No.3

Analysis and modeling of industrial energy are currently a time-insertion process because more and more energy is consumed for economic growth in an industrial factory. Industrial energy consumption analysis and prediction play a very important role in improving the energy utilization rate to make profitable things for industrial companies or factories. Industrial factory owners are also starting to realize the importance of energy analysis and predictions to make a plan for better energy utilization for their factories. So, this is the high time to work as a technological supportive hand with an industrial factory in order to improve their energy utilization for making some profitable things for industrial organizations and also for our society. It is not so easy process to analyses energy and realizes accurate predictions of industrial energy consumption. Therefore, this study deals with analysing total usages of 24-hours energy consumption for every month and also total usages of energy for the year 2017. We find out the difference between total usages of energy and demands of energy for the year 2017. We make relation curve between per-day usages of energy and different types of materials weight for different types of manufacturing product, and also make a relation curve between per-day usages of energy, demands of energy and total materials weight for manufacturing products for the year 2017. We use the correlation method to find out the relationship of usages of energy with different types of materials weight for manufacturing products. Finally, we find out the total usages of energy for manufacturing every product and make a decision about the energy utilization.

A Comparative Study Based on SVR for the Change of Strawberry Productions by the Variation of Nutrient Water Flow

A.B.M. Salman Rahman,이명배,Vasanth Ragu,조용윤,박장우,신창선 한국지식정보기술학회 2019 한국지식정보기술학회 논문지 Vol.14 No.3

Strawberry is one of the most well-liked fruits all over the world, and strawberry productions is rapidly rising as one of the most healthy economies all over the world. Due to the high demand for strawberries, greenhouse strawberry cultivation is increasing rapidly and farmers are using different types of methods for greenhouse cultivation to get high productions. The aims of this study are to find out the high production rate of the strawberry based on nutrient solutions with water flow rate. Farmers use a different amount of water nutrient solutions for strawberry production but mostly they don’t know how much nutrient solutions with water flow is good for getting high production because of giving the high amount or less amount of nutrient solutions with water flow are always not good or bad for productions. Farmers have to know about the amount of nutrient solutions with water flow for getting good productions and now this is the high time to support farmers for increasing their strawberry productions by giving technological support. Therefore, in this study, we analyze the production rate of strawberries based on the nutrient solutions with water flow rate of strawberries in every bed. Finally, through the results and discussion by using the support vector regression model we find out that how much nutrient solutions with water flow should be needed to obtain high yielding of strawberries.

An Analysis Study Based on Linear Regression Model for Changes of Fruit Size over Plum Diseases

A.B.M. Salman Rahman,Ragu Vasanth,이명배,박장우,조용윤,이명훈,신창선 한국지식정보기술학회 2018 한국지식정보기술학회 논문지 Vol.13 No.5

There are different types of diseases occur in plants and fruits due to the changes of not only the climate, weather, and seasons, but also the environmental factors like temperature, humidity, and rainfall etc. Diseases can change the structure of plants, fruits and also crops. The influence of plants and fruits disease affects our agriculture industry and agriculture sector. Diseases can interrupt our plant’s growth, fruits growth, production growth, and also makes an effect on economic growth all over the world. Farmers have a lot of experience in detecting problems and also they can identify the diseases in various plants. They can easily take care or actions for environmental factorial diseases but sometimes it’s not working. Technologies can support farmers to make their methods more reliable to improve farmer’s crops and fruits quality for a good production. Therefore in this study, we analyse different types of plum plant diseases and then use the linear regression model to know the condition of plum fruit size using plum growth, plum length and plum width. In result and discussion, we identify the environment factorial diseases in plum and also make a decision by verifying the plum fruits size after diseases occurred in Plum Plants.

온실 운영 비용을 고려한 복합환경 관리 시스템

이명배 ( Myeongbae Lee ),박철영 ( Chulyung Park ),조현욱 ( Hyunwook Cho ),바산트 ( Vasanth Ragu ),배석환 ( Seokhwan Bae ),박장우 ( Jangwoo Park ),조용윤 ( Yongyun Cho ),신창선 ( Changsun Shin ) 한국정보처리학회 2017 한국정보처리학회 학술대회논문집 Vol.24 No.1

본 논문은 온실의 내/외부 환경 요소 및 시장정보 등의 외적 요소를 반영하여 농가의 작물 생산 비용을 고려하여 생장지표와 목표점을 설정함으로써 온실의 운용비용을 절감하고, 데이터 분석 및 PID 제어를 통해 효율성과 신뢰성을 높일 수 있는 온실 복합환경 관리 시스템에 대한 연구이다.