• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.2
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• pp.177-186
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• 2021

This paper aims to show that cooperative robots, which have only been used in manufacturing sites, are expanding their scope of use in daily living spaces due to the expansion of non-face-to-face services. By combining robots and IoT technologies in terms of diversifying services in daily life and customized service areas, it is expected that the general public will also have easy access to smart technologies, and these technologies will be used in more areas. The robot barista system will provide customers with the services they want, monitoring, maintenance, and management of the system, making this paper convenient for customers, as well as managers who run stores, maintenance and repair, and engineers who design the system. This paper attempts to demonstrate this through a structure called Robopresso.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.533-535
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• 2021

The differences between this study and previous studies are as follows. First, by building a cloud-based system using IoT technology, the system was built to monitor the status of buildings in real time from anywhere with an internet connection. Second, a model for predicting the future was developed using artificial intelligence (LSTM) and statistical (ARIMA) methods for the measured time series sensor data, and the effectiveness of the proposed prediction model was experimentally verified using a scaled-down building model. Third, a method to analyze the condition of a building more three-dimensionally by visualizing the structural deformation of a building by convergence of multiple sensor data was proposed, and the effectiveness of the proposed method was demonstrated through the case of an actual earthquake-damaged building.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.49-55
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• 2019

An open office or a shared office is emerging as the emphasis on the collaborative and communicative work environments is increasing. In the past, the user maintained the space, but the maintenance of indoor space became difficult because there is no fixed user. Indoor space information can be collected using the ICBM framework system. The facility management can achieve this with data. Therefore, this study proposed a framework based on ICBM (Internet of Things, Cloud, Big Data, and Mobile) for verifying the possibility of a smart facility management system for indoor space. IoT (Internet of Things) technology was used to measure the indoor temperature, humidity, occupancy, and brightness continuously, and provided the data to Web API via WiFi. Data acquired automatically via IoT, existing maintenance data, and spatial information were integrated through the Cloud. Big data collected by sensors were processed as meaningful spatial information for maintenance. Indoor space information and maintenance information can be delivered to the manager through the mobile. Based on the collected data, room occupancy recognition is limited due to a range of ultrasonic wave sensors. On the other hand, brightness represents the space conditions. The difference between lighting on/off, weekday and weekend can be shown. The temperature data and the relative humidity data were collected steadily to evaluate the comfort.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.4
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• pp.121-128
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• 2021

In order to design a real time big data collection and analysis system of manufacturing data in a smart factory, it is important to establish an appropriate wired/wireless communication system and protocol. This paper introduces the latest communication protocol, OPC-UA (Open Platform Communication Unified Architecture) based client/server function, applied user interface technology to configure a network for real-time data collection through IoT Integration. Then, Database is designed in MES (Manufacturing Execution System) based on the analysis table that reflects the user's requirements among the data extracted from the new cutting process automation process, bush inner diameter indentation measurement system and tool monitoring/inspection system. In summary, big data analysis system introduced in this paper performs SPC (statistical Process Control) analysis and visualization analysis with interface of OPC-UA-based wired/wireless communication. Through AI learning modeling with XGBoost (eXtream Gradient Boosting) and LR (Linear Regression) algorithm, quality and visualization analysis is carried out the storage and connection to the cloud.

• Journal of Korea Multimedia Society
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• v.23 no.3
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• pp.421-429
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• 2020

Recently, with the development of IoT technology and the increase of energy consumption, interest in energy saving and energy efficiency improvement is rapidly increasing. In particular, in the case of a device connected to a power plug with the power shutoff, a problem with standby power has been raised. Thus technology development through a low power method such as Zigbee is in progress. However, Zigbee, which is generally used, has a problem that a separate gateway is required because it is not an IP-based technology, and there is a problem that it is not suitable for a traditional computer network to which a variety of devices are connected. Therefore, in this paper, we designed and implemented a standby power saving system using MQTT, an IoT standard protocol, in Z-Wave environment. In order to evaluate the implemented standby power saving system, the same environment as the existing Zigbee-based standby power saving system was compared and evaluated.

• Journal of the Korea Convergence Society
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• v.13 no.1
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• pp.387-398
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• 2022

This paper presents a system that remotely monitors lone seniors at home and promptly alarms caregivers to recommend appropriate medical care services upon detecting abnormal behavior and critical conditions such as collapsing, excessive coughing, degradation of sleep quality, fever, and unusual indoor moving lines. Our system offers contactless monitoring techniques based on heterogeneous IoT sensors and deep learning to minimize the disruption to lone senior's daily life. In addition to the design and implementation of the sensor data collection and analysis system, we share our experience in installation, deployment, configuration, maintenance of the system through the case study conducted on the actual lone seniors living in Seoul Metropolitan. Based on our research, we recommend further development directions to prepare for the nationwide expansion of our system.

• Journal of information and communication convergence engineering
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• v.16 no.1
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• pp.31-37
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• 2018

In this work, we propose an analytic framework for evaluating the quality of service and dimensioning the link capacity in the gateway router of a smart farm with a greenhouse eco-management system. Specifically, we focus on the gateway router of an IoT network that provides an access service for smart farms. We design the link capacity of a gateway router that is used for the remote management of the greenhouse eco-management system to accommodate both time-critical and delay-tolerant traffic in a greenhouse LAN. For this purpose, we first investigate the ecosystem for smart farm, and we define the specification and requirements of the greenhouse eco-management system. Second, we propose a system model for the link capacity of a gateway that is required to guarantee the delay performance of time-critical applications in the greenhouse LAN. Finally, the validity of the proposed system is demonstrated through a series of numerical experiments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.3
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• pp.974-992
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• 2021

Recently, the healthcare field has undergone rapid changes owing to the accumulation of health big data and the development of machine learning. Data mining research in the field of healthcare has different characteristics from those of other data analyses, such as the structural complexity of the medical data, requirement for medical expertise, and security of personal medical information. Various methods have been implemented to address these issues, including the machine learning model and cloud platform. However, the machine learning model presents the problem of opaque result interpretation, and the cloud platform requires more in-depth research on security and efficiency. To address these issues, this paper presents a recent technology for Internet-of-Things-based (IoT-based) health big data processing. We present a cloud-based IoT health platform and health big data processing technology that reduces the medical data management costs and enhances safety. We also present a data mining technology for health-risk prediction, which is the core of healthcare. Finally, we propose a study using explainable artificial intelligence that enhances the reliability and transparency of the decision-making system, which is called the black box model owing to its lack of transparency.

• Journal of Industrial Convergence
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• v.20 no.8
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• pp.61-67
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• 2022

The Internet of Things(IoT) is one of the key technologies in the Fourth Industrial Revolution. The IoT is a system that acquires information from various sensors and provides meaningful information to users. The method of obtaining information from sensor is using WIFI, Bluetooth and Server. is not accessible to external users because of different type of networks or local area communication. For this reason, there is a problem that external user cannot receive notification in regard to sensor information. In this paper, we want to establish a cloud message environment using Google's FCM(Firebase Cloud Messaging) and find out through experiments how users can receive notifications even if they are outside.

• Journal of the Society of Disaster Information
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• v.15 no.1
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• pp.39-48
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• 2019

Purpose: This study aims at developing and implementing Smart Safety Management System based on IoT/ICT Convergence for safety of high-risk groups working at disaster or industrial field. Its functions are as follows. Method: We will develop three devices for keeping the safety of high-risk jobs: Sensor of inactivity, Lora based Refitting technology for communication between high-risk workers, and Lora Gateway for monitoring entire situations. Then we will test three devices in respect of their functions, and propose their applicabilities in the field. Results: The system can send and receive safety tags and danger signals by which sensor technology can detect dangerous state of workers. And its command terminal was developed by low-power wireless communication technology and LoRa Gateway, which can fulfill the lifting functions between safety tags. And, furthermore, the command terminal can monitor dangerous situations of disaster sites in real time and can perform the preemptive rescues. Conclusion: This study proves the functional efficacy of Smart Safety Management System for worker safety in various high-risk occupational groups, and also suggests ways to secure worker safety in disaster area and various high risk industrial sites.