• The Journal of the Korea Contents Association
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• v.19 no.12
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• pp.9-17
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• 2019

The Internet of Things (IoT) is a technology that connects to the Internet with built-in sensors and communication functions on various objects and has been used in various fields such as smart home and smart factory. Recently, as interest in air pollution information such as fine dust is increasing, the apps for providing weather information and air pollution information based on IoT technology are being developed. In this study, we aims to provide visual air pollution and weather information and develop useful services such as appliance automation using this information. for this study, we designed and implemented Smart Services that provide home automation, messaging and alarm, visual air pollution and weather information using air pollution and weather information based on IoT.

• Journal of the Korean Solar Energy Society
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• v.37 no.6
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• pp.103-114
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• 2017

Radiation energy budget was analyzed using observation data from the Weather Information Service Engine (WISE) energy flux tower on the Seoul metropolitan area. Among observation data from the 13 energy flux towers, we used meteorological variables, radiation data (upward and downward short wave, upward and downward long wave, net short wave, net long wave and net radiation), albedo and emissivity for 15 months from July 2016 to September 2017. Although Gajwa (205) and Ttuksumm (216) sites located in urban, the albedo was relatively high due to the surround environment by glass wall buildings and the Han river around the sites. And Bucheon (209) site located in the suburb represented generally low emissivity. As a result, the albedo decreased and the emissivity increased in the city center. In the Seoul metropolitan area, the net radiation energy is $73.9W/m^2$ that the radiation budget of the surface is absorbed into the atmosphere. According to WISE observation data, it can be seen that observation at each sites are influenced by the surrounding environment.

• Agribusiness and Information Management
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• v.6 no.1
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• pp.1-11
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• 2014

The purpose of this study is to develop the growth prediction model that can predict growth and development information influencing on the production of citrus fruits. The growth model was developed to predict the floral leaf ratio, number of fruit sets, fruit width, and overweight fruits depending on the main period of growth and development by considering the weather factors because the fruit production is influenced by weather depending on the growth and development period. To predict the outdoor-grown citrus fruit production, the investigation result for the standard farms is used as the basic data; in this study, we also understood that the influence of weather factors on the citrus fruit production based on the data from 2004 to 2013 of the outdoor-grown citrus fruit observation report in which the standard farms were targeted by the Agricultural Research Service and suggested the growth and development information prediction model with the weather information as an independent variable to build the observation model. The growth and development model for outdoor-grown citrus fruits was assumed by using the Ordinary Least Square method (OLS), and the developed growth prediction model can make a prediction in advance with the weather factors prior to the observation investigation for the citrus fruit production. To predict the growth and development information of the production of citrus fruits having a great ripple effect as a representative crop in Jeju agriculture, the prediction result regarding the production applying the weather factors depending on growth and development period could be applied usefully.

• The KIPS Transactions:PartC
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• v.15C no.2
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• pp.93-102
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• 2008

The network weather map and bandwidth time-series graph are popularly used to understand the current and past traffic condition of NSP, ISP, and enterprise networks. These systems collect traffic performance data from a SNMP agent running on the network devices such as routers and switches, store the gathered information into a DB, and display the network performance status in the form of a time-series graph or a network weather map using Web user interface. Most of current enterprise networks are constructed in the form of a hierarchical tree-like structure with multi-Gbps Ethernet links, which is quietly different from the national or world-wide backbone network structure. This paper focuses on the network weather map for current enterprise network. We start with the considering points in developing a network weather map system suitable for enterprise network. Based on these considerings, this paper proposes the best way of using SNMP in constructing a network weather map system. To prove our idea, we designed and developed a network weather map system for our campus network, which is also described in detail.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.6C
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• pp.398-402
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• 2011

High resolution windspeed profile measurements are needed in a weather radar to provide the reliable information of rapidly changing weather conditions. However, it is necessary to remove both stationary and moving clutter to obtain the accurate pulse pair estimates. To overcome these problems, a simple adaptive array antenna may be applied to clutter removal. Using the simulated weather and clutter data, the clutter cancellation capability is analyzed for a weather radar with an adaptive antenna. The pulse pair estimates obtained from the adaptive weather radar are compared with those of the raw data.

• Journal of Environmental Science International
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• v.27 no.7
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• pp.509-518
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• 2018

Weather is the most influential factor for crop cultivation. Weather information for cultivated areas is necessary for growth and production forecasting of agricultural crops. However, there are limitations in the meteorological observations in cultivated areas because weather equipment is not installed. This study tested methods of predicting the daily mean temperature in onion fields using geostatistical models. Three models were considered: inverse distance weight method, generalized additive model, and Bayesian spatial linear model. Data were collected from the AWS (automatic weather system), ASOS (automated synoptic observing system), and an agricultural weather station between 2013 and 2016. To evaluate the prediction performance, data from AWS and ASOS were used as the modeling data, and data from the agricultural weather station were used as the validation data. It was found that the Bayesian spatial linear regression performed better than other models. Consequently, high-resolution maps of the daily mean temperature of Jeonnam were generated using all observed weather information.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.4
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• pp.764-768
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• 2006

In this paper, the importance of an information communication and weather information system is presented. The technology on a weather information system setup which may provide the ubiquitous to the foundation is investigated. A number of crucial technology implementation of a future weather information system and the time to be realized is estimated. Based on the research on numerous literatures on the topic, in addition, the practical usage strategy of the proposed weather system is presented.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.2
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• pp.493-500
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• 2011

Recently, there has been an increase in the number of disaster victims locally due to climate change and a variety of frequently occurring natural disasters. The damage caused by abrupt weather change in local area by typical weather forecasting techniques is very limited and difficult. Recently local area weather monitoring system using wireless sensor network technology has been very actively studied. Thus an IEEE 802.15.4-based weather field server to measure and monitor the local weather changes was designed and developed in this study. The proposed weather field server utilizes a wireless sensor node and weather sensors to collect weather information such as temperature, humidity, illumination, dew point, barometric pressure, and water level. The integrated weather sensor board was designed to respond quickly to weather changes, and provide feedback to the server PC. Each weather information is analyzed in the server PC to establish a program to monitor and analyze the local area or the area of abrupt climate change in order to provide warning signals in case of disaster events in local.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.3
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• pp.393-398
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• 2015

City or Community-scale Energy Management System(CEMS) is used to reduce the total energy consumed in the city by arranging the energy resources efficiently at the planning stage and controlling them economically at the operating stage. Of the operational functions of the CEMS, generation forecasting of renewable energy resources is an essential feature for the effective supply scheduling. This is because it can develop daily operating schedules of controllable generators in the city (e.g. diesel turbine, micro-gas turbine, ESS, CHP and so on) in order to minimize the inflow of the external power supply system, considering the amount of power generated by the uncontrollable renewable energy resources. This paper is written to introduce numerical models for photo-voltaic power generation prediction based on the weather forecasting information. Unlike the conventional methods using the average radiation or average utilization rate, the proposed models are developed for CEMS applications using the realtime weather forecast information provided by the National Weather Service.

• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.219-224
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• 2022

The Korea Meteorological Administration(KMA) has been released life-related indexes such as 'Life industrial weather information' and 'Safety weather information' while other countries' meteorological administrations have been made 'Human-biometeorology' and 'Health meteorology' indexes that concern human sensibility effections to diverse criteria. Although human sensibility changes have been studied in psychological research criteria with diverse and innumerous application areas, there are not enough studies that make data mining based validation of sensibility change factors. In this research I made models to estimate sensibility change caused by weather factors such as temperature and humidity, and validated by collecting sensibility data from SNS text crawling and weather data from KMA public dataset. By Logistic Regression, I clarify factors affecting sensibility changes.