• IEIE Transactions on Smart Processing and Computing
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• v.4 no.5
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• pp.354-365
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• 2015

This work presents an Internet of Things (IoT) system for home energy management based on a custom-designed Impulse Radio Ultra-Wideband (IR-UWB) transceiver that targets a generic and multi-standard control system. This control system enables the interoperability of heterogeneous devices: it integrates various sensor nodes based on ZigBee, EnOcean and UWB in the same middleware by utilizing an ad-hoc layer as an interface between the hardware and software. The paper presents as a first the design of the IR-UWB transceiver for a portable sensor node integrated with the middleware layer, and also describes the receiver connected to the control system. The custom-designed low-power transmitter on the sensor node is fabricated with 130 nm CMOS technology. It generates a signal with a 1.1 ns pulse width while consuming $39{\mu}W$ at 1 Mbps. The UWB sensor node with a temperature measurement capability consumes 5.31 mW, which is lower than the power level of state-of-the-art solutions for smart-home applications. The UWB hardware and software layers necessary to interface with the control system are verified in over-the-air measurements in an actual office environment. With the implementation of the presented sensor node and its integration in the energy management system, we demonstrate achievement of the broad flexibility demanded for IoT.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.3
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• pp.741-746
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• 2015

Recently, as mobile operating system market and wireless communication technology have been rapidly developed, many devices such as smart phones, air conditioners, smart TVs, cleaning robot, and cameras become available with android operating system. Accordingly, collecting variety of information through many everyday use devices with network connections is now enabled. However, in the current market, most devices are controlled individually developed applications, and there is growing need to develop a master application that can control multiple devices. In this paper, we propose and implement a system that can control multiple android-based devices on a Wired/Wireless router(AP) registered through web server. we expect such an effort can attribute to future IoT researches.

• IEMEK Journal of Embedded Systems and Applications
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• v.11 no.2
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• pp.97-105
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• 2016

Microcontrollers (MCUs) for endpoint smart sensor devices of internet-of-thing (IoT) are being implemented as system-on-chip (SoC) with on-chip instruction flash memory, in which user firmware is embedded. MCUs directly fetch binary code-based instructions through bit-line sense amplifier (S/A) integrated with on-chip flash memory. The S/A compares bit cell current with reference current to identify which data are programmed. The S/A in reading '0' (erased) cell data consumes a large sink current, which is greater than off-current for '1' (programmed) cell data. The main motivation of our approach is to reduce the number of accesses of erased cells by binary code level transformation. This paper proposes a built-in write/read path architecture using binary code inversion method based on hot-spot region detection of instruction code access to reduce sensing current in S/A. From the profiling result of instruction access patterns, hot-spot region of an original compiled binary code is conditionally inverted with the proposed bit-inversion techniques. The de-inversion hardware only consumes small logic current instead of analog sink current in S/A and it is integrated with the conventional S/A to restore original binary instructions. The proposed techniques are applied to the fully-custom designed MCU with ARM Cortex-M0$^{TM}$ using 0.18um Magnachip Flash-embedded CMOS process and the benefits in terms of power consumption reduction are evaluated for Dhrystone$^{TM}$ benchmark. The profiling environment of instruction code executions is implemented by extending commercial ARM KEIL$^{TM}$ MDK (MCU Development Kit) with our custom-designed access analyzer.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.4
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• pp.758-767
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• 2017

IoT paradigm which makes a information without direct intervention of a human and interworks with other objects, humans and systems is attracting attention. It will be expected the number of smart devices equipped with sensors and wireless communication capabilities is reached to about 260 billion by 2020. With the vast amount of sending data generated from rapidly increasing number of smart devices, it will bring up the traffic growth over internet and congestion in wireless networks. In this paper, we utilize the smart device as a sink node to collect and forward the sensing data periodically in IoT and propose a heuristic algorithm for a selection of sink nodes' set with each sink node satisfies the QoS its applications because a selection of optimal sink nodes' set is NP-hard problem. The complexity of proposed heuristic algorithm is $O(m^3)$ and faster than the optimal algorithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.206-209
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• 2018

According to data released by the WHO(World Health Organization), the death toll from indoor air pollution in 2016 was about 3.8 million. While many people are aware of outdoor air pollution, indoor air pollution is getting less attention. Recently, however, indoor air pollution has also become a big problem, raising many issues. Frequent indoor activities such as cooking and heating produce various pollutants, which can cause children and elderly with weak immune systems to be exposed to pollutants, which can cause serious health problems such as poor lung function and respiratory diseases. Therefore, in this paper, the IoT(Internet of Things) platform that measures and monitors indoor air quality using AQ(Air Quality) sensors is developed so that data can be monitored in real time through applications and reactive web.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.7
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• pp.2209-2224
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• 2022

The Internet of Things (IoT) is being used in a wide variety of fields due to the recent 4th industrial revolution. In particular, research is being conducted that combines IoT with the medical field such as telemedicine. Among them, the field of shock detection is a big issue in the medical field because the causes of shock are diverse, treatments are very complex, and require a high level of medical knowledge and experience. The transmission of infectious diseases is common when treating critically ill patients, especially patients with shock. Thus, to effectively care for shock patients, we propose an architecture that continuously monitors the patient's condition, and automatically recommends a drug injection treatment according to the patient's shock condition. The patient's hemodynamic information is continuously monitored, and the patient's shock generation information is recorded periodically. With the recorded patient information, the patient's condition is determined and automatically injected with necessary medication. The medical team can find out whether the patient's condition has improved by checking the recorded information through web applications. The study can help relieve the shortage of medical personnel and help prevent transmission of infectious disease in medical staff. We look forward to playing a role in helping medical staff by making recommendations for the diagnosis and treatment of complex and difficult shocks.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.313-316
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• 2021

In the IoT(IoT: Internet of Things) environment, network configuration is essential to collect data generated from objects. Various communication methods are used to process data of objects, and wireless communication methods such as Bluetooth and WiFi are mainly used. In order to collect data of objects, a communication module must be installed to collect data generated from sensors or edge devices in real time. And in order to deliver data to the database, a software architecture must be configured. Data generated from objects can be stored and managed in a database in real time, and data necessary for industrial safety can be extracted and utilized for industrial safety service applications. In this paper, a network environment was constructed using a LoRa(LoRa: Long Range) gateway to collect object data, and a client/server data collection model was designed to collect object data transmitted from the LoRa module. In order to secure the resources necessary for data collection and storage management without data leakage, data collection should be possible in real time. As an application service, location data required for industrial safety can be stored and managed in a database in real time.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2017.11a
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• pp.1437-1451
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• 2017

4차 산업혁명의 주요 기술 중 하나로 언급되는 사물인터넷 기술은 헬스케어분야에서 질병의 예측, 관리뿐만 아니라 보건의료 산업 전반에까지 영향을 미치고 있으며, 기술의 고도화 및 적용 분야가 점차 확대되고 있다. 이에 본고에서는 사물인터넷이 헬스케어 산업 분야에 적용 동향을 살펴보고, 한국, 미국, 일본, 유럽 특허청의 특허분석을 통해 공백 기술 및 분야에 대한 분석과 함께 향후 기술 개발이 요구되는 분야에 대해 논하고자 한다.

• International Journal of Advanced Culture Technology
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• v.9 no.3
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• pp.315-320
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• 2021

Currently, cloud computing is being used as a technology that greatly changes the IT field. For many businesses, many cloud services are available in the form of custom, reliable, and cost-effective web applications. Most cloud service providers provide functions such as IoT, machine learning, AI services, blockchain, AR & VR, mobile services, and containers in addition to basic cloud services that support the scalability of processors, memory, and storage. In this paper, we will look at the most used cloud service providers and compare the services provided by the cloud service providers.

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.237-245
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• 2022

The prominence of IoTs (Internet of Things) and exponential advancement of computer networks has resulted in massive essential applications. Recognizing various cyber-attacks or anomalies in networks and establishing effective intrusion recognition systems are becoming increasingly vital to current security. MLTs (Machine Learning Techniques) can be developed for such data-driven intelligent recognition systems. Researchers have employed a TFDNNs (Tensor Flow Deep Neural Networks) and DCNNs (Deep Convolution Neural Networks) to recognize pirated software and malwares efficiently. However, tuning the amount of neurons in multiple layers with activation functions leads to learning error rates, degrading classifier's reliability. HTFDNNs ( Hybrid tensor flow DNNs) and MRNs (Modified Residual Networks) or Resnet CNNs were presented to recognize software piracy and malwares. This study proposes HTFDNNs to identify stolen software starting with plagiarized source codes. This work uses Tokens and weights for filtering noises while focusing on token's for identifying source code thefts. DLTs (Deep learning techniques) are then used to detect plagiarized sources. Data from Google Code Jam is used for finding software piracy. MRNs visualize colour images for identifying harms in networks using IoTs. Malware samples of Maling dataset is used for tests in this work.