• Journal of Digital Policy
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• v.1 no.2
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• pp.1-8
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• 2022

In case of a dangerous situation, the roof, which serves as an emergency exit, must be open in case of fire according to the Fire Act. However, when the roof door is opened, it has become a place of various incidents and accidents such as illegal entry, crime, and suicide. As a result, it is a reality to close the roof door in terms of facility management to prevent crime, various incidents, and accidents. Accordingly, the government is pushing to legislate regulations on housing construction standards, etc. that mandate the installation of electronic automatic opening and closing devices on rooftop doors. Therefore, in this paper, an intelligent emergency door opening/closing device system is proposed. To this end, an intelligent emergency door opening and closing system was developed by linking wired and wireless access counting and AI image analysis. Finally, it is possible to build a wireless communication-based integrated management platform that provides remote control and history management in a centralized method of device status real-time monitoring and event alarm.

• PNF and Movement
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• v.22 no.1
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• pp.43-54
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• 2024

Purpose: Falls among persons older than 65 years are a significant concern due to their frequency and severity. This study aimed to develop a vest-type embedded artificial intelligence (AI) system capable of detecting and predicting falls in various scenarios. Methods: In this study, we established and developed a vest-type embedded AI system to judge and predict falls in various directions and situations. To train the AI, we collected data using acceleration and gyroscope values from a six-axis sensor attached to the seventh cervical and the second sacral vertebrae of the user, considering accurate motion analysis of the human body. The model was constructed using a neural network-based AI prediction algorithm to anticipate the direction of falls using the collected pedestrian data. Results: We focused on developing a lightweight and efficient fall prediction model for integration into an embedded AI algorithm system, ensuring real-time network optimization. Our results showed that the accuracy of fall occurrence and direction prediction using the trained fall prediction model was 89.0% and 78.8%, respectively. Furthermore, the fall occurrence and direction prediction accuracy of the model quantized for embedded porting was 87.0 % and 75.5 %, respectively. Conclusion: The developed fall detection and prediction system, designed as a vest-type with an embedded AI algorithm, offers the potential to provide real-time feedback to pedestrians in clinical settings and proactively prepare for accidents.

• Journal of Platform Technology
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• v.9 no.1
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• pp.32-39
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• 2021

Existing environmental measuring devices mainly focus on electromagnetic wave and eco-friendly product certification and durability test, and sensor reliability verification and verification of measurement data are conducted mainly through sensor performance evaluation through type approval and registration, acceptance test, initial calibration, and periodic test. This platform has established an ICT-based environmental monitoring sensor reliability verification system that supports not only performance evaluation for each target sensor, but also a verification system for sensor data reliability. A sensor board to collect sensor data for environmental information was produced, and a sensor and data reliability evaluation and verification service system was standardized. In addition, to evaluate and verify the reliability of sensor data based on ICT, a sensor data platform monitoring prototype using LoRa communication was produced, and the test was conducted in smart cities. To analyze the data received through the system, an optimization algorithm was developed using machine learning. Through this, a sensor big data analysis system is established for reliability verification, and the foundation for an integrated evaluation and verification system is provide.

• Journal of Animal Science and Technology
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• v.61 no.3
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• pp.163-169
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• 2019

Detection of estrus is an essential factor as a method of successful breeding in the sow. As increasing the adaption of the information and communication technology (ICT) into swine industry, this study focuses on a possibility and quantification of standing time, vulva and body temperature as methods of estrus detection, comparing each time and temperature in estrus and non-estrus period, and analyzing each success rate of new and existing methods. Ultrasonic sensor array and digital infrared thermography were used to evaluate whether new methods such as standing time and number, and vulva and skin temperature can be replaced, or these methods can be quantifiable in estrus period. Ultrasonic sensor array was installed beside the stall and digital infrared thermography was placed in the rear of sow to collect the dates of sow in estrus and non-estrus period. This study showed total standing time, number and number over 10 minutes, and vulva temperature of the sow in estrus period were increased (p < 0.05) compared with those of sow in non-estrus period, respectively. Detection of estrus using standing time and vulva temperature tended (p = 0.06) to increase the success rate when artificial insemination (AI) was performed. In conclusion, standing time and vulva temperature increased when estrus happened. Success rate of AI of sow using these methods showed an increasing trend. Therefore, existing method using the naked eye can be replaced to new method such as vulvar temperature and standing time when detecting the estrus.

• The Journal of the Korea Contents Association
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• v.22 no.1
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• pp.47-57
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• 2022

Demands for tangible contents using VR/AR technologies are much bigger as contactless services such as sports, physical activity, and fitness are expanded after COVID-19. A variety of technologies such as an offer and analysis of tangible data through a sensor technology, users' physical movement sensing through a motion recognition sensor, a real-time measurement of a physical skeleton point a multiple access to a real-time video, and AI training are being utilized as main technologies. This case study utilized motion recognition technologies as the study on tangible contents necessary for indoor-based physical education, sports, and fitness in the contactless environment and suggested cases to develop the physical measurement contents by design approach for the measurement assessment necessary for the development in tangible contents. The research established lists of the measurement assessment based on professionals' consultations within the measurement assessment function through the test to plan tangible contents and developed tangible contents by reflecting them as assessment measurement elements of tangible contents. The research can be utilized as the design approach of industrial companies which intend to develop tangible contents as well as reference cases of the research on contactless tangible contents for the sports and physical education.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.41-42
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• 2021

The Green New Deal policy was established to innovate the government's energy consumption structure, establish a third basic energy plan to strengthen the global competitiveness of the energy industry, and realize a carbon neutral society due to the increased need for transition to a low-carbon economy. Waterworks such as drinking water, water purification plant, and pressurization plant analyze control factors and energy consumption status by process to improve energy management efficiency and reduce energy usage through the 4th industrial revolution. Ultimately, we want to realize net-zero water purification plant.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.11
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• pp.247-249
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• 2020

In the era of the 4th industrial revolution, the demand for convergence between ICT technologies is increasing in various fields. Accordingly, a new term that combines data, network, and artificial intelligence technology, DNA (Data, Network, AI) is in use. and has recently become a hot topic. DNA has various potential technology to be able to develop intelligent application in the real world. Therefore, this paper introduces the reviewed papers on the service image placement mechanism based on the logical fog network, the mobility support scheme based on machine learning for Industrial wireless sensor network, the prediction of the following BCI performance by means of spectral EEG characteristics, the warning classification method based on artificial neural network using topics of source code and natural language processing model for data visualization interaction with chatbot, related on DNA technology.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.2
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• pp.125-134
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• 2022

Recently, there are an increased the number of reports on the misuse or malicious use of an UAS. Thus, many researchers are studying on defense schemes for UAS by developing or improving C-UAS sensor technology. However, the wrong placement of sensors may lead to a defense failure since the proper placement of sensors is critical for UAS defense. In this study, a multi-object optimization model for C-UAS sensor placement in an air base is proposed. To address the issue, we define two objective functions: the intersection ratio of interested area and the minimum detection range and try to find the optimized placement of sensors that maximizes the two functions. C-UAS placement model is designed using a NSGA-II algorithm, and through experiments and analyses the possibility of its optimization is verified.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.67-68
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• 2023

본 논문에서 제안한 Multi Agent Multi Action은 기존의 대화형 시스템 방식인 Single Agent Single Action 구조에 비해 확장성을 갖춘 대화 시스템을 구현하는 방식이다. 시스템을 여러 에이전트로 분할하고, 각 에이전트가 특정 액션에 대한 처리를 담당함으로써 보다 유연하고 효율적인 대화형 시스템을 구현할 수 있으며, 다양한 작업에 특화된 에이전트를 그룹화함으로써 작업의 효율성을 극대화하고, 사용자 경험을 향상 시킬 수 있다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.96-106
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• 2020

To solve the limitation of traffic monitoring that occur from embedded sensor such as loop and piezo sensors, the thermal imaging camera was installed on the roadside. As the length of Class 1(passenger car) is getting longer, it is becoming difficult to classify from Class 3(2-axle truck) by using an embedded sensor. The collected images were labeled to generate training data. A total of 17,536 vehicle images (640x480 pixels) training data were produced. CNN (Convolutional Neural Network) was used to achieve vehicle classification based on thermal image. Based on the limited data volume and quality, a classification accuracy of 97.7% was achieved. It shows the possibility of traffic monitoring system based on AI. If more learning data is collected in the future, 12-class classification will be possible. Also, AI-based traffic monitoring will be able to classify not only 12-class, but also new various class such as eco-friendly vehicles, vehicle in violation, motorcycles, etc. Which can be used as statistical data for national policy, research, and industry.