• Journal of the Korea Institute of Building Construction
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• v.21 no.1
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• pp.21-29
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• 2021

The objective of this study is to evaluate the effect of the application of double layered bubble sheet on the curing of slab and wall concrete placed at the job site in cold weather and to offer a feasibility of Concrete IoT Management System(CIMS), which is wireless sensor network developed by the authors, to manage early age quality of the concrete in terms of temperature, maturity and strength development. Test results indicated that the application of bubble sheet enhances the insulation performance, which results in an increase of the temperature by around 1~20. 6℃. It is found that CIMS can gather the temperature, maturity and strength development data from the sensors embedded from 30 m far from CIMS successfully. Predicted compressive strengths by CIMS had good agreement with measured ones within 2 MPa error level until 7 days. It is thought that the combination of the bubble sheet application for cold weather protection and CIMS for quality management tool in cold weather concreting contributes to shorten the time for the form removal by one day.

• Journal of Korea Multimedia Society
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• v.18 no.6
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• pp.772-779
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• 2015

Advancing information technology have rapidly changed our service environment of life, culture, and industry. Computer information communication system is applied in medical, health, distribution, and business transaction. Smart is using new information by combining ability of computer and information. Although agriculture is labor intensive industry that requires a lot of hands, agriculture is becoming knowledge-based industry today. In agriculture field, computer communication system is applied on facilities farming and machinery Agricultural. In this paper, we designed and implemented application that provides personalized agriculture related information at the actual farming field. Also, this provides farmer a system that they can directly auction or sell their produced crops. We designed and implemented a system that parsing information of each seasonal, weather condition, market price, region based, crop, and disease and insects through individual setup on ubiquitous environment using location-based sensor network and processing data.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.2
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• pp.233-237
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• 2010

The recent advance of sensor networks and ubiquitous techniques allow collecting and analyzing of the data which overcome the limitation imposed by time and space in real-time for making decisions. Also, analysis and prediction of collected data can support useful and necessary information to users. The collected data in sensor networks environment is the stream data which has continuous, unlimited and sequential properties. Because of the continuous, unlimited and large volume properties of stream data, managing stream data is difficult. And the stream data needs dynamic processing method because of the memory constraint and access limitation. Accordingly, we analyze correlation stream data using principal component analysis. And using result of analysis, it helps users for making decisions.

• ETRI Journal
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• v.38 no.3
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• pp.551-559
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• 2016

In this paper, we propose a hybrid sensor calibration scheme for mobile crowdsensing applications. As the number of newly produced mobile devices containing embedded sensors continues to rise, the potential to use mobile devices as a sensor data source increases. However, because mobile device sensors are generally of a lower performance and cost than dedicated sensors, sensor calibration is crucial. To enable more accurate measurements of natural phenomena through the use of mobile device sensors, we propose a hybrid sensor calibration scheme for such sensors; the scheme makes use of mobile device sensors and existing sensing infrastructure, such as weather stations, to obtain dense data. Simulation results show that the proposed scheme supports low mean square errors. As a practical application of our proposed scheme, we built a temperature map of a city using six mobile phone sensors and six reference sensors. Thanks to the mobility of the sensors and the proposed scheme, our map presents more detailed information than infrastructure-based measurements.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.4
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• pp.729-738
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• 2022

Existing wardrobes have been used only for storing simple clothes. Since it has a function to store clothes, there is only one way to control the environment such as humidity or temperature, and there is only one way to purchase and store items such as a desiccant. In this paper, by increasing the convenience in the existing wardrobe, automatic temperature and humidity control and various convenient functions were added. In line with the smart home market and smart phone application market that have grown over the past several years, along with the development of a wardrobe with sensors, the temperature and humidity control function and other functions inside the wardrobe through Bluetooth pairing between the wardrobe and the smartphone can be customized to the user using a smartphone. Through the clothing selection function and the weather data in the application, we want to implement convenient functions such as the function of recommending clothes in the closet to match the weather.

• Korean Journal of Remote Sensing
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• v.32 no.3
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• pp.263-274
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• 2016

In this study, we compared the Precipitable Water Vapor (PWV) data derived from the radiosonde observation at Sokcho observatory and the PWV data at Sokcho Global Navigation Satellite System (GNSS) observatory provided by Korea Astronomy and Space Science Institute, for the summer of 2007~2014, and analyzed the radiosonde diurnal and rainfall-dependent bias according to radiosonde sensor types. In the scatter diagram of the daytime and nighttime radiosonde PWV data and GNSS PWV data, dry bias was found in the daytime radiosonde observation as known in the previous study and dry bias of RSG-20A sensor was larger than other sensors. Overall, the tendency that the wet bias of the radiosonde PWV increased as GNSS PWV decreased and the dry bias of the radiosonde PWV increased as GNSS PWV increased. The quantitative analysis of the bias and error of the radiosonde PWV data showed that the mean bias decreased in the nighttime except for 2007, 2008 summer. In comparison for summer according to the presence or absence of rainfall, RS92-SGP sensor showed the highest quality.

• Journal of Korea Society of Digital Industry and Information Management
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• v.7 no.1
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• pp.1-9
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• 2011

In this paper, Wireless sensor network technology applied to various greenhouse agro-industry items such as horticulture and local specialty etc., we was constructed automatic control system for optimum growth environment by measuring growth status and environmental change. existing monitoring systems of greenhouse gather information about growth environment depends on the temperature. but in this system, Can be efficient collection and control of information to construct wireless sensor network by growth measurement sensor and environment monitoring sensor inside of the greenhouse. The system is consists of sensor manager for information processing, an environment database that stores information collected from sensors, the GUI of show the greenhouse status, it gather soil and environment information to soil and environment(including weather) sensors, growth measurement sensor. In addition to support that soil information service shows the temperature, moisture, EC, ph of soil to user through the interaction of obtained data and Complex Growth Environment information service for quality and productivity can prevention and response by growth disease or disaster of greenhouse agro-industry items how temperature, humidity, illumination acquiring informationin greenhouse(strawberry, ginseng). To verify the executability of the system, constructing the complex growth environment measurement system using wireless sensor network in greenhouse and we confirmed that it is can provide our optimized growth environment information.

• Journal of Korea Multimedia Society
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• v.23 no.8
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• pp.1006-1018
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• 2020

Dataset is getting more import to develop a learning based algorithm. Quality of the algorithm definitely depends on dataset. So we introduce new dataset over 200 thousands images which are fully labeled multi modal sensor data. Proposed dataset was designed and constructed for researchers who want to develop detection, tracking, and action classification in outdoor environment for surveillance scenarios. The dataset includes various images and multi modal sensor data under different weather and lighting condition. Therefor, we hope it will be very helpful to develop more robust algorithm for systems equipped with difference kinds of sensors in outdoor application. Case studies with the proposed dataset are also discussed in this paper.

• Journal of Environmental Science International
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• v.27 no.11
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• pp.1155-1167
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• 2018

We developed a small sensor observation system (SSOS) at a relatively low cost to observe the atmospheric boundary layer. The accuracy of the SSOS sensor was compared with that of the automatic weather system (AWS) and meteorological tower at the Korea Meteorological Administration (KMA). Comparisons between SSOS sensors and KMA sensors were carried out by dividing into ground and lower atmosphere. As a result of comparing the raw data of the SSOS sensor with the raw data of AWS and the observation tower by applying the root-mean-square-error to the error, the corresponding values were within the error tolerance range (KMA meteorological reference point: humidity ${\pm}5%$, atmospheric pressure ${\pm}0.5hPa$, temperature ${\pm}0.5^{\circ}C$. In the case of humidity, even if the altitude changed, it tends to be underestimated. In the case of temperature, when the altitude rose to 40 m above the ground, the value changed from underestimation to overestimation. However, it can be confirmed that the errors are within the KMA's permissible range after correction.

• Journal of KIISE
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• v.41 no.9
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• pp.686-698
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• 2014

Recently, large-scale streaming sensor data have emerged due to explosive supply of smart phones, diffusion of IoT and Cloud computing technology, and generalization of IoT devices. Also, researches on combination of semantic web technology are being actively pushed forward by increasing of requirements for creating new value of data through data sharing and mash-up in large-scale environments. However, we are faced with big issues due to large-scale and streaming data in the inference field for creating a new knowledge. For this reason, we propose the RDFS rule based parallel reasoning scheme to service by processing large-scale streaming sensor data with the semantic web technology. In the proposed scheme, we run in parallel each job of Rete network algorithm, the existing rule inference algorithm and sharing data using the HBase, a hadoop database, as a public storage. To achieve this, we implement our system and evaluate performance through the AWS data of the weather center as large-scale streaming sensor data.