• Title/Summary/Keyword: Internet of small things

Search Result 136, Processing Time 0.025 seconds

Design and Implementation of Remote Device Management System based on LoRa Communication (LoRa 통신기반 원격 장비 관리 시스템 설계 및 구현)

  • Kim, Dong-Hyun;Lee, Chang-Hong;Kim, Jong-Deok
    • Journal of the Korea Institute of Information and Communication Engineering
    • /
    • v.24 no.12
    • /
    • pp.1654-1661
    • /
    • 2020
  • Internet of Things(IoT) technology can remotely collect and control a sensing information of device by attaching a small communication device to equipment that does not support communication. Low-Power Wide-Area Network (LPWAN), a low-power, long-distance communication technology, was proposed to support IoT technology, and Long Range(LoRa) is representative. Various systems, including network device, can collect and control the status information of device in real time through remote access. However, when a network failure occurs, remote access and status monitoring are impossible unless there is a separate additional network. To overcome this problem, in this paper, we propose an independent remote device management system that can be easily attached to device, which monitors and controls equipment remotely using an independent network. We will design and implement the proposed system, via which we will show its practicality and expandability.

Network Topology Discovery with Load Balancing for IoT Environment (IoT환경에서의 부하 균형을 이룬 네트워크 토폴로지 탐색)

  • Park, Hyunsu;Kim, Jinsoo;Park, Moosung;Jeon, Youngbae;Yoon, Jiwon
    • Journal of KIISE
    • /
    • v.44 no.10
    • /
    • pp.1071-1080
    • /
    • 2017
  • With today's complex networks, asset identification of network devices is becoming an important issue in management and security. Because these assets are connected to the network, it is also important to identify the network structure and to verify the location and connection status of each asset. This can be used to identify vulnerabilities in the network architecture and find solutions to minimize these vulnerabilities. However, in an IoT(Internet of Things) network with a small amount of resources, the Traceroute packets sent by the monitors may overload the IoT devices to determine the network structure. In this paper, we describe how we improved the existing the well-known double-tree algorithm to effectively reduce the load on the network of IoT devices. To balance the load, this paper proposes a new destination-matching algorithm and attempts to search for the path that does not overlap the current search path statistically. This balances the load on the network and additionally balances the monitor's resource usage.

A Study on the Vulnerability Management of Internet Connection Devices based on Internet-Wide Scan (인터넷 와이드 스캔 기술 기반 인터넷 연결 디바이스의 취약점 관리 구조 연구)

  • Kim, Taeeun;Jung, Yong Hoon;Jun, Moon-Seog
    • Journal of the Korea Academia-Industrial cooperation Society
    • /
    • v.20 no.9
    • /
    • pp.504-509
    • /
    • 2019
  • Recently, both wireless communications technology and the performance of small devices have developed exponentially, while the number of services using various types of Internet of Things (IoT) devices has also massively increased in line with the ongoing technological and environmental changes. Furthermore, ever more devices that were previously used in the offline environment-including small-size sensors and CCTV-are being connected to the Internet due to the huge increase in IoT services. However, many IoT devices are not equipped with security functions, and use vulnerable open source software as it is. In addition, conventional network equipment, such as switches and gateways, operates with vulnerabilities, because users tend not to update the equipment on a regular basis. Recently, the simple vulnerability of IoT devices has been exploited through the distributed denial of service (DDoS) from attackers creating a large number of botnets. This paper proposes a system that is capable of identifying Internet-connected devices quickly, analyzing and managing the vulnerability of such devices using Internet-wide scan technology. In addition, the vulnerability analysis rate of the proposed technology was verified through collected banner information. In the future, the company plans to automate and upgrade the proposed system so that it can be used as a technology to prevent cyber attacks.

A Combined Random Scalar Multiplication Algorithm Resistant to Power Analysis on Elliptic Curves (전력분석 공격에 대응하는 타원곡선 상의 결합 난수 스칼라 곱셈 알고리즘)

  • Jung, Seok Won
    • Journal of Internet of Things and Convergence
    • /
    • v.6 no.2
    • /
    • pp.25-29
    • /
    • 2020
  • The elliptic curve crypto-algorithm is widely used in authentication for IoT environment, since it has small key size and low communication overhead compare to the RSA public key algorithm. If the scalar multiplication, a core operation of the elliptic curve crypto-algorithm, is not implemented securely, attackers can find the secret key to use simple power analysis or differential power analysis. In this paper, an elliptic curve scalar multiplication algorithm using a randomized scalar and an elliptic curve point blinding is suggested. It is resistant to power analysis but does not significantly reduce efficiency. Given a random r and an elliptic curve random point R, the elliptic scalar multiplication kP = u(P+R)-vR is calculated by using the regular variant Shamir's double ladder algorithm, where l+20-bit u≡rn+k(modn) and v≡rn-k(modn) using 2lP=∓cP for the case of the order n=2l±c.

IoT-based Dangerous Zone Alarming System for Safety Management in Construction Sites (건설 현장 안전관리를 위한 IoT 기반의 위험구역 경보 시스템)

  • Kim, Seung-Ho;Kang, Chang-Soon;Ryu, HanGuk
    • Journal of the Korea Convergence Society
    • /
    • v.10 no.10
    • /
    • pp.107-115
    • /
    • 2019
  • Effective construction safety management systems are desperately required for reducing damage caused by increasing safety accidents in construction sites. Safety accidents in construction sites can effectively protect if proactive measures are taken to prevent unauthorized worker access the expected hazardous area. In this study, we have developed a IoT(Internet of Things)-based dangerous zone alarming system for safety management in construction sites, which can be operated at low cost in large-scale sites as well as small and medium-sized construction sites. The development system utilizes a Zigbee-based beacon technology and cellular mobile communication technology to detect when authorized workers, unauthorized field workers or outsiders approaches hazardous zones. If somebody approaches the dangerous zones the system notifies immediately to the safety manager with a danger warning signal. It is expected that this system can effectively prevent safety accidents when applied to construction sites.

Deep Learning-Based Smart Meter Wattage Prediction Analysis Platform

  • Jang, Seonghoon;Shin, Seung-Jung
    • International journal of advanced smart convergence
    • /
    • v.9 no.4
    • /
    • pp.173-178
    • /
    • 2020
  • As the fourth industrial revolution, in which people, objects, and information are connected as one, various fields such as smart energy, smart cities, artificial intelligence, the Internet of Things, unmanned cars, and robot industries are becoming the mainstream, drawing attention to big data. Among them, Smart Grid is a technology that maximizes energy efficiency by converging information and communication technologies into the power grid to establish a smart grid that can know electricity usage, supply volume, and power line conditions. Smart meters are equient that monitors and communicates power usage. We start with the goal of building a virtual smart grid and constructing a virtual environment in which real-time data is generated to accommodate large volumes of data that are small in capacity but regularly generated. A major role is given in creating a software/hardware architecture deployment environment suitable for the system for test operations. It is necessary to identify the advantages and disadvantages of the software according to the characteristics of the collected data and select sub-projects suitable for the purpose. The collected data was collected/loaded/processed/analyzed by the Hadoop ecosystem-based big data platform, and used to predict power demand through deep learning.

Strategies of smart factory building and Application of small & medium-sized manufacturing enterprises (스마트팩토리 구축전략과 중소.중견 제조기업의 적용 방안)

  • Park, Jong-Shik;Kang, Kyung-sik
    • Journal of the Korea Safety Management & Science
    • /
    • v.19 no.1
    • /
    • pp.227-236
    • /
    • 2017
  • Smart Manufacturing Factory is a paradigm of the future lead to the fourth industrial revolution that led Germany and the United States. Now the automation of the production facility and won a certain degree, and through the process of integrating the entire process, including planning, design, distribution of information and communication technology products in emerging as a core competitiveness of the national economy. In particular, the company accelerated the smart factory building in order to improve the manufacturing industry, cost savings and productivity simply to incorporate internet of things(IoT),Robot, artificial intelligence, big data technology as a factory automation level of sophistication of the system and out to progress to the level that replaces human labor have. In this we should look at the trend of promoting domestic and foreign factories want to present these smart strategies for Korea.

Breath Gas Sensors for Diabetes and Lung Cancer Diagnosis

  • Byeongju Lee;Jin-Oh Lee;Junyeong Lee;Inkyu Park;Dae-Sik Lee
    • Journal of Sensor Science and Technology
    • /
    • v.32 no.1
    • /
    • pp.1-9
    • /
    • 2023
  • Recently, the digital healthcare technologies including non-invasive diagnostics based on Internet of Things (IOT) are getting attention. Human exhaled breath contains a variety of volatile organic compounds (VOCs), which can provide information of malfunctions of the body and presence of a specific disease. Detection of VOCs in exhaled breath using gas sensors are easy to use, safe, and cost-effective. However, accurate diagnosis of diseases is challenging because changes in concentration of VOCs are extremely small and lots of body factors directly or indirectly influence to the conditions. To overcome the limitations, highly selective nanosensors and artificial intelligent electronic nose (E-nose) systems have been mainly researched in recent decades. This review provides brief reviews of the recent studies for diabetes and lung cancer diagnosis using nanosensors and E-nose systems.

WiFi-Based Home IoT Communication System

  • Chen, Wenhui;Jeong, Sangho;Jung, Hoekyung
    • Journal of information and communication convergence engineering
    • /
    • v.18 no.1
    • /
    • pp.8-15
    • /
    • 2020
  • Internet-of-Things (IoT) technologies are used everywhere, and communication is one of its core and essential aspect. To solve the networking and communication of small IoT terminals, in this paper, a communication scheme based on low-cost WiFi is proposed, which also has the advantages of good compatibility and low power consumption. At the same time, it has a convenient one-key configuration mode, which reduces the technical requirements for operators. In this study, a communication protocol is designed that mainly aims at up to dozens of domestic IoT terminals, in which the amount of data is not large, data exchange is not high, and network is unstable. According to the alarm data, update data, and equipment or network fault, the protocol can respectively transmit in real time, regularly and repeatedly. This protocol is open and easy to integrate, and after cooperating with tiny encryption algorithm, information can be safely transmitted.

Security, Privacy, and Efficiency of Sustainable Computing for Future Smart Cities

  • Jeong, Young-Sik;Park, Jong Hyuk
    • Journal of Information Processing Systems
    • /
    • v.16 no.1
    • /
    • pp.1-5
    • /
    • 2020
  • Sustainable computing is a rapidly expanding field of research covering the fields of multidisciplinary engineering. With the rapid adoption of Internet of Things (IoT) devices, issues such as security, privacy, efficiency, and green computing infrastructure are increasing day by day. To achieve a sustainable computing ecosystem for future smart cities, it is important to take into account their entire life cycle from design and manufacturing to recycling and disposal as well as their wider impact on humans and the places around them. The energy efficiency aspects of the computing system range from electronic circuits to applications for systems covering small IoT devices up to large data centers. This editorial focuses on the security, privacy, and efficiency of sustainable computing for future smart cities. This issue accepted 17 articles after a rigorous review process.