• International conference on construction engineering and project management
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• 2022.06a
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• pp.353-360
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• 2022

Due to the dense and complicated working environment, the construction industry is susceptible to many accidents. Worker's fall is a severe problem at the construction site, including falling into holes or openings because of the inadequate coverings as per the safety rules. During the construction or demolition of a building, openings and holes are formed in the floors and roofs. Many workers neglect to cover openings for ease of work while being aware of the risks of holes, openings, and gaps at heights. However, there are safety rules for worker safety; the holes and openings must be covered to prevent falls. The safety inspector typically examines it by visiting the construction site, which is time-consuming and requires safety manager efforts. Therefore, this study presented a worker-driven approach (the worker is involved in the reporting process) to facilitate safety managers by developing integrated computer vision and inertia sensors-based mobile applications to identify openings. The TensorFlow framework is used to design Convolutional Neural Network (CNN); the designed CNN is trained on a custom dataset for binary class openings and covered and deployed on an android smartphone. When an application captures an image, the device also extracts the accelerometer values to determine the inclination in parallel with the classification task of the device to predict the final output as floor (openings/ covered), wall (openings/covered), and roof (openings / covered). The proposed worker-driven approach will be extended with other case scenarios at the construction site.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.559-561
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• 2022

In order to secure the stability of tap water production and supply, we have built a system that can be pre-verified before applying AI-based composite sensors to the water purification plant, which is a demonstration site. We have collected and analyzed data related to the drug input of the GO-RYEONG water purification plant for about two years from December 2019 to December 2021. The outliers of each tag were removed through data preprocessing such as outliers and derived variable, and the cycle was set as average data for 60 minutes of each one-minute period, and the model was learned using the PLS model.

• Journal of the Korean Geographical Society
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• v.36 no.2
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• pp.126-140
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• 2001

The influence of small urban parks(green ratio is 100%) on the temperature pattern over the urban and its surrounding area was examined by analyzing the case of in and around Changkyeong palace, Changdeok plalace and Jongmyo, Jongro-gu, Seoul. The pattern of temperature over urban parks and their surrounding built-up area was analyzed from September to November 2000, measuring maximum and minimum temperatures with fixed sensors(maximum and minimum thermometer)and real-time temperature depends largely on both the land-use type and the distance from the park border. In the case of maximum temperature, the lowest value appeared on the green area within parks and the highest value on the built-up area far from the green area. The maximum temperature difference between parks and built-up areas was up to $7.3^{\circ}C$. In the built-up area, the maximum temperature of commercial areas was higher than residential areas. In the night time, not only land-use type but also topography is important for the spatial distributlon of temperature because of the cold airflow from adjacet hills. The horizontal temperature profile by mobile measurement is also related to land-use type and to the distance from the park borders. There is a magnitude of $1^{\circ}C$ temperture difference over a distance of 200m and $3~4^{\circ}C$ over a distance of 400m from the park borders.

• Journal of the Korea institute for structural maintenance and inspection
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• v.15 no.4
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• pp.165-174
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• 2011

This research aims at the optimal constitution of sensors required to identify the structural shortcoming of roller-coaster. In this research we analyzed the dynamic characteristics of roller-coaster by three dimensional FE modelling, decided on the appropriate location and number of sensors through optimal transducer theory, abstracted the mathematical value of modal features before and after damage on the basis of optimally placed and numbered sensors. and then presented it as a primary information about the basic structure which would be applied to damage estimation. As a target structure, the roller-coater at Seoul Children's Grand Park was chosen and built as a model reduced by one twentieth in size. In order to consider the Kinetics features particular to the roller-coaster structure, we made an exact three-dimensional FE modelling for the model structure by means of Spline function. As for the proper location and number of sensors, it was done by applying EIM and EOT. We also estimated the damage from the combination of strength, flexibility, and model corelation after abstracting the value of modal features. Finally the optimal transducer theory presented here in this research was proved to be valid, and the structural damage was well identified through changes in strength and flexibility. As a result, we were able to present the optimal constitution of sensors needed for the analysis of dynamic characteristics and the development of techniques in dynamic characteristics, which would ultimately contribute to the development of health monitoring for roller-coaster.

• Journal of Wetlands Research
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• v.22 no.4
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• pp.312-320
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• 2020

Various LIDs with natural water circulation function are applied to reduce urban environmental problems and environmental impact of development projects. However, excessive Infiltration and evaporation of LID facilities dry the LID internal soil, thus reducing plant and microbial activity and reducing environmental re duction ability. The purpose of this study was to develop a real-time measurement system with complex sensors to derive the management plan of LID facilities. The test of measurable sensors and Internet of Things (IoT) application was conducted in artificial wetlands shaped in acrylic boxes. The applied sensors were intended to be built at a low cost considering the distributed LID and were based on Arduino and Raspberry Pi, which are relatively inexpensive and commercialized. In addition, the goal was to develop complex sensor measurements to analyze the current state o f LID facilities and the effects of maintenance and abnormal weather conditions. Sensors are required to measure wind direction, wind speed, rainfall, carbon dioxide, Micro-dust, temperature and humidity, acidity, and location information in real time. Data collection devices, storage server programs, and operation programs for PC and mobile devices were developed to collect, transmit and check the results of measured data from applied sensors. The measurements obtained through each sensor are passed through the Wifi module to the management server and stored on the database server in real time. Analysis of the four-month measurement result values conducted in this study confirmed the stability and applicability of ICT technology application to LID facilities. Real-time measured values are found to be able to utilize big data to evaluate the functions of LID facilities and derive maintenance measures.

• Proceedings of the KSR Conference
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• 2007.11a
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• pp.989-993
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• 2007

It was intended in this study to seek for the measures to utilize the USN technique, which has high usability due to low price and low power consumption, in air quality monitoring. As a method, the sensors of temperature, humidity, particulate matters (PM10), and carbon dioxide ($CO_2$) were installed in the self-manufactured sensor nodes; the nodes were installed in the waiting rooms and platforms of a subway station and the measurements were collected at real time with use of a computer which micro gateway was built in. Collected data was to be processed by the statistics program installed in the computer; the collected data is to be used in managing the air quality of stations after transmission to the ventilation system of ventilation chambers.

• Proceedings of the KIPE Conference
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• 1998.10a
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• pp.386-391
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• 1998

Parameter estimation method of induction motor for vector control is presented in this paper. It can be easily implemented and applied to inverters in the industrial field, because it needs no additional hardware such as voltage sensors and measuring equipment. The proposed algorithm in this paper is so straightforward and practical that it can be easily implemented on the built-in controllers with little overhead. The proposed estimation algorithm has good accuracy and repeatability for parameters due to the sensitivity of estimation errors. This enables its total consuming time to be made shorter. Experimental results and applications in the industrial fields verify the validity and usefulness of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1830-1835
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• 2003

A novel index representing burden distribution form in the blast furnace is developed and index estimation model is built with an empirical modeling method to monitor inner condition of the furnace without expensive sensors. To find the best combination of index and modeling method, two candidates for the index and four modeling methods have been examined. Results have shown that 3-D index have more resolution in describing the distribution form than 1-D index and ANN model produces smallest RMSE due to nonlinearity between the indices and charging mode. Although ANN has shown the best prediction accuracy in this study, PLS can be a good alternative due to its advantages in generalization capability, consistency, simplicity and training time. The second best result of PLS in the prediction results supports this fact.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2002.05a
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• pp.39-43
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• 2002

As the concept of the smart structure, monitoring of acoustic emission (AE) can be applied to inspect the fracture of the entire structure in operating condition using built-in sensors. The objective of this study is to find the characteristics of matrix crack signals in composites due to the different specimen shapes. To detect matrix crack signals, we performed tensile tests by changing the thickness, width and length of the specimen. For the quantitative evaluation, time frequency analysis such as short-time Fourier transform (STFT) was used to characterize the matrix crack signals from PZT sensor. The experimental result shows the distinctive signal features in frequency domain due to the different specimen shapes.

• Journal of the Korea Society of Computer and Information
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• v.24 no.5
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• pp.59-66
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• 2019

According to the KT telecommunication statistics, people stayed inside their houses on an average of 11.9 hours a day. As well as, according to NSC statistics in the united states, people regardless of age are injured for a variety of reasons in their houses. For purposes of this research, we have investigated an abnormal event detection algorithm to classify infrequently occurring behaviors as accidents, health emergencies, etc. in their daily lives. We propose a fusion method that combines three classification algorithms with vision pattern, audio pattern, and activity pattern to detect unusual user events. The vision pattern algorithm identifies people and objects based on video data collected through home CCTV. The audio and activity pattern algorithms classify user audio and activity behaviors using the data collected from built-in sensors on their smartphones in their houses. We evaluated the proposed individual pattern algorithm and fusion method based on multiple scenarios.