• Journal of the Institute of Convergence Signal Processing
• /
• v.21 no.3
• /
• pp.142-147
• /
• 2020

The Internet of Things is valuable as a means of solving social problems such as personal, public, and industrial. Recently, the application of IoT technology to the healthcare industry is increasing. It is important to ensure reliability and security in IoT-based healthcare services. Communication protocols, wireless transmit/receive techniques, and reliability-based message delivery are essential elements in IoT healthcare devices. The system was designed and implemented to measure body temperature and activity through body temperature and acceleration sensors and deliver them to the oneM2M-based Mobius platform.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2021.11a
• /
• pp.1320-1323
• /
• 2021

최근 미래형 농업으로 주목받고 있는 '아쿠아포닉스(Aquaponics)'는 물고기 양어 기술(Aquaculture)과 수경 농법(Hydroponic)을 융합한 친환경적인 순환형 생산 시스템이다. 하지만 양식 환경과 수경재배환경이 서로 성장하는 데에 영향을 주기 때문에 농업인이나 일반인이 사용하기에 난도가 높고, 초기 투자비가 많이 든다는 점에서 국내 도입에 대한 문제점이 제기되고 있다.[1] 본 논문에서는 IoT 기술을 이용해 아쿠아포닉스의 단점을 보완할 기술적 대안과 국내 도입 문제 해결방안으로서 오토팜(AutoFarm) 시스템을 제안한다.

• Journal of Convergence for Information Technology
• /
• v.10 no.8
• /
• pp.53-59
• /
• 2020

This paper relates to an IoT device system that detects sound source and estimates the sound source location. More specifically, it is a system using a sound source direction detection device that can accurately detect the direction of a sound source by analyzing the difference of arrival time of a sound source signal collected from microphone sensors, and track the generation direction of a sound source using an IoT sensor. As a result of a performance test by generating a sound source, it was confirmed that it operates very accurately within 140dB of the acoustic detection area, within 1 second of response time, and within 1° of directional angle resolution. In the future, based on this design plan, we plan to commercialize it by improving the reliability by reflecting the artificial intelligence algorithm through big data analysis.

• Journal of the Semiconductor & Display Technology
• /
• v.18 no.3
• /
• pp.122-126
• /
• 2019

These-days technology related to IoT (Internet of Thing) is widely used and there are many types of smart system based IoT like smart health, smart building and so on. In smart health system, it is possible to check someone's health by analyzing data from wearable IoT device like smart watch. Smart building system aims to collect data from sensor such as humidity, temperature, human counter like that and control the building for energy efficiency, security, safety and so forth. Furthermore, smart city system can comprise several smart systems like smart building, smart health, smart mobility, smart energy and etc. In this paper, we propose multimedia IoT based intelligent emergency alarm system for smart city. In existing IoT based smart system, it communicates lightweight data like text data. In the past, due to network's limitations lightweight IoT protocol was proposed for communicating data between things but now network technology develops, problem which is to communicate heavy data is solving. The proposed system obtains video from IP cameras/CCTVs, analyses the video by exploiting AI algorithm for detecting emergencies and prevents them which cause damage or death. If emergency is detected, the proposed system sends warning message that emergency may occur to people or agencies. We built prototype of the intelligent emergency alarm system based on MQTT and assured that the system detected dangerous situation and sent alarm messages. From the test results, it is expected that the system can prevent damages of people, nature and save human life from emergency.

• Journal of Internet of Things and Convergence
• /
• v.7 no.1
• /
• pp.1-7
• /
• 2021

The IoT market continues to expand and grow, but the security threat to IoT devices is also increasing. However, it is difficult to apply the security technology applied to the existing system to IoT devices that have a problem of resource limitation. Therefore, in this paper, we present a service that can improve the security of IoT devices by presenting authentication and lightweight cryptographic algorithms that can reduce the overhead of applying security features, taking into account the nature of resource limitations of IoT devices. We want to apply these service to home network IoT equipment to provide security. The authentication and lightweight cryptographic algorithm application protocols presented in this paper have secured the safety of the service through the use of LEA encryption algorithms and secret key generation by users, IoT devices and server in the IoT environment. Although there is no difference in speed from randomly generating secret keys in experiments, we verify that the problem of resource limitation of IoT devices can be solved by additionally not applying logic for secret key sharing to IoT devices.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2023.11a
• /
• pp.151-153
• /
• 2023

Federated learning (FL)-based network intrusion detection techniques have enormous potential for securing the Industrial Internet of Things (IIoT) cybersecurity. The openness and connection of systems in smart industrial facilities can be targeted and manipulated by malicious actors, which emphasizes the significance of cybersecurity. The conventional centralized technique's drawbacks, including excessive latency, a congested network, and privacy leaks, are all addressed by the FL method. In addition, the rich data enables the training of models while combining private data from numerous participants. This research aims to create an FL-based architecture to improve cybersecurity and intrusion detection in IoT networks. In order to assess the effectiveness of the suggested approach, we have utilized well-known cybersecurity datasets along with centralized and federated machine learning models.

• Journal of the Institute of Convergence Signal Processing
• /
• v.23 no.4
• /
• pp.216-221
• /
• 2022

The 4th industrial revolution is accelerating the transition to digital innovation in various aspects of our daily lives, and efforts for manufacturing innovation are continuing in the manufacturing industry, such as smart factories. The 4th industrial revolution technology in manufacturing can be used based on AI, big data, IoT, cloud, and robots. Through this, it is required to develop a technology to establish a production facility data collection and analysis system that has evolved from the existing automation and to find the cause of defects and minimize the defect rate. In this paper, we implemented a system that collects power, environment, and status data from production facility sites through IoT devices, quantifies them in real-time in a cloud computing environment, and displays them in the form of MQTT-based real-time infographics using widgets. The real-time sensor data transmitted from the IoT device is stored to the cloud server through a Rest API method. In addition, the administrator could remotely monitor the data on the dashboard and analyze it hourly and daily.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2022.11a
• /
• pp.764-766
• /
• 2022

본 시스템은 스마트폰에서 사용자의 음성을 이용해 집 안이나 밖에서 IoT 단말을 효율적으로 제어할 수 있는 시스템으로, 인식된 음성에 맞춰 가전제품 기동, 조명 조절 등 IoT 단말을 컨트롤한다. 사용자의 음성은 Json 형태의 명령으로 변환되어 에지 컴퓨팅 기술을 통해 저사양 단말이 고사양 단말의 유휴자원을 활용하며 명령에 따른 IoT 단말 컨트롤이 진행된다. 이러한 아키텍처는 IoT 단말 데이터를 외부에 노출하지 않고 컴퓨팅 자원을 효율적으로 운용할 수 있는 시스템을 제공한다.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.14 no.4
• /
• pp.787-796
• /
• 2019

In this paper, we propose the design and test measure of Ringer injection IoT system for controling the ringer injection status and notifying the server system of the collected status informations such as the completion of injection, the remaining liquid, the injection status, and the emergency alarming of the urgent patients. We design the circuit diagrams composed of linger injection sensors, switches, status indicators, wireless communication functionalities, and propose the controlling and monitoring algorithms for sensing the linger injection status and notifying the collected status informations to a server system. Furthermore, we derive the testing criteria, such as linger liquid sensing time, sensing distance, operating temperature, input power, power consumption, and wireless communication speed, and analyze the test results.

• International journal of advanced smart convergence
• /
• v.12 no.2
• /
• pp.173-181
• /
• 2023

Data collection is an essential element in the construction and operation of a smart factory. The quality of data collection is greatly influenced by network conditions, and existing wireless network systems for IoT inevitably lose data due to wireless signal strength. This data loss has contributed to increased system instability due to misinformation based on incorrect data. In this study, I designed a distributed MQTT IoT smart sensor and gateway structure that supports wireless multicasting for smooth sensor data collection. Through this, it was possible to derive significant results in the service latency and data loss rate of packets even in a wireless environment, unlike the MQTT QoS-based system. Therefore, through this study, it will be possible to implement a data collection management system optimized for the domestic smart factory manufacturing environment that can prevent data loss and delay due to abnormal data generation and minimize the input of management personnel.