• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
• /
• v.8 no.6
• /
• pp.909-917
• /
• 2018

Recently, the Internet of Thing (IoT) technology is expanding explosively in the number of devices and applications in many application areas. In IoT systems, sensors and actuators are connected to the Internet and cooperate to do some applications by exchanging information. In this paper an IoT smart home system is developed to monitor and control home devices easily. Our system consists of sensor devices, IoT gateways, and an IoT server. Sensor devices developed using Rfduino sense the physical world and transmit their data using BLE to the IoT server thru the IoT gateway. We implemented the IoT gateway using Raspberry Pi and the IoT server using ARTIK cloud. We installed our system and made a test in our lab, which showed that our system can be installed and managed easily and extended its functionality in an easy way. By taking advantage of the rule mechanism and action messages of ARTIK cloud, we implemented the control of device parameters easily by sending action messages to the ARTIK cloud.

• KIPS Transactions on Computer and Communication Systems
• /
• v.9 no.12
• /
• pp.291-306
• /
• 2020

Nowadays, Data-Network-AI (DNA)-based intelligent services and applications have become a reality to provide a new dimension of services that improve the quality of life and productivity of businesses. Artificial intelligence (AI) can enhance the value of IoT data (data collected by IoT devices). The internet of things (IoT) promotes the learning and intelligence capability of AI. To extract insights from massive volume IoT data in real-time using deep learning, processing capability needs to happen in the IoT end devices where data is generated. However, deep learning requires a significant number of computational resources that may not be available at the IoT end devices. Such problems have been addressed by transporting bulks of data from the IoT end devices to the cloud datacenters for processing. But transferring IoT big data to the cloud incurs prohibitively high transmission delay and privacy issues which are a major concern. Edge computing, where distributed computing nodes are placed close to the IoT end devices, is a viable solution to meet the high computation and low-latency requirements and to preserve the privacy of users. This paper provides a comprehensive review of the current state of leveraging deep learning within edge computing to unleash the potential of IoT big data generated from IoT end devices. We believe that the revision will have a contribution to the development of DNA-based intelligent services and applications. It describes the different distributed training and inference architectures of deep learning models across multiple nodes of the edge computing platform. It also provides the different privacy-preserving approaches of deep learning on the edge computing environment and the various application domains where deep learning on the network edge can be useful. Finally, it discusses open issues and challenges leveraging deep learning within edge computing.

• Journal of Internet Computing and Services
• /
• v.19 no.1
• /
• pp.37-47
• /
• 2018

The number of capabilities of Internet of Things (IoT) devices will exponentially grow over the next years. These devices may generate a vast amount of time-constrained data. In the context of IoT, data management should act as a layer between the objects and devices generating the data and the applications accessing the data for analysis purposes and services. In addition, most of IoT services will be content-centric rather than host centric to increase the data availability and the efficiency of data delivery. IoT will enable all the communication devices to be interconnected and make the data generated by or associated with devices or objects globally accessible. Also, fog computing keeps data and computation close to end users at the edge of network, and thus provides a new breed of applications and services to end users with low latency, high bandwidth, and geographically distributed. In this paper, we propose Edge-Fog cloud-based Hierarchical Data Delivery ($EFcHD^2$) method that effectively and reliably delivers IoT data to associated with IoT applications with ensuring time sensitivity. The proposed $EFcHD^2$ method stands on basis of fully decentralized hybrid of Edge and Fog compute cloud model, Edge-Fog cloud, and uses information-centric networking and bloom filters. In addition, it stores the replica of IoT data or the pre-processed feature data by edge node in the appropriate locations of Edge-Fog cloud considering the characteristic of IoT data: locality, size, time sensitivity and popularity. Then, the performance of $EFcHD^2$ method is evaluated through an analytical model, and is compared to fog server-based and Content-Centric Networking (CCN)-based data delivery methods.

• International Journal of Computer Science & Network Security
• /
• v.22 no.3
• /
• pp.45-52
• /
• 2022

To make the research and development in IoT networks witness a significant improvement and last for a long period, it is always important to attract new researchers to work on this area and be a part of it. The best way to attract researchers to work in any research area and have their interest is to give them a clear background and roadmap about it. In this way, researchers can easily find a deep point to start their research based on their interest. This paper presents an overview and roadmap about IoT technologies from the most five vital aspects: IoT architecture, communication technologies, type of IoT applications, IoT applications protocols and IoT challenges.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.24 no.12
• /
• pp.1688-1696
• /
• 2020

The paradigm of Internet-of-things(IoT) systems is changing from a cloud-based system to an edge-based system to solve delays caused by network congestion, server overload and security issues due to data transmission. However, edge-based IoT systems have fatal weaknesses such as lack of performance and flexibility due to various limitations. To improve performance, application-specific hardware can be implemented in the edge device, but performance cannot be improved except for specific applications due to a fixed function. This paper introduces a edge-centric metamorphic IoT(mIoT) platform that can use a variety of hardware through on-demand partial reconfiguration despite the limited hardware resources of the edge device, so we can increase the performance and flexibility of the edge device. According to the experimental results, the edge-centric mIoT platform that executes the reconfiguration algorithm at the edge was able to reduce the number of server accesses by up to 82.2% compared to previous studies in which the reconfiguration algorithm was executed on the server.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.65 no.12
• /
• pp.2232-2239
• /
• 2016

IoT industry has been highlighted in the domestic and foreign country. Since most IoT systems operate separate servers in Internet to control IoT hardwares, there exists the possibility of security problems. Also, IoT systems in markets use their own hardware controllers and devices. As a result, there are many limitations in adding new sensors or devices and using applications to access hardware controllers. To solve these problems, we have developed a novel IoT hardware control system based on a mobile messenger. For the security, we have adopted a secure mobile messenger, Telegram, which has its own security protection. Also, it can improve the easy of the usage without any installation of specific applications. For the enhancement of the system accessibility, the proposed IoT system supports various network protocols. As a result, there are many possibility to include various functions in the system. Finally, our IoT system can analyze the collected information from sensors to provide useful information to the users. Through the experiment, we show that the proposed IoT system can perform well.

• Journal of Multimedia Information System
• /
• v.9 no.3
• /
• pp.209-218
• /
• 2022

Industrial IoT applications, including smart factories, require two problem-solving to build data monitoring systems required by services from distributed IoT sensors (smart sensors). One is to overcome proprietary protocols, data formats, and hardware differences and to uniquely identify and connect IoT sensors, and the other is to overcome the problem of changing the server-side data storage structure and sensor data transmission format according to the addition or change of service or IoT sensors. The IEEE 1451.4 standard-based or IPMI specification-based smart sensor technology supports the development of plug-and-play sensors that solve the first problem. However, there is a lack of research that requires a second problem-solving, which requires support for the plug-in of IoT sensors into remote services. To propose a solution for the integration of these two problem-solving, we present a IoT sensor platform, a service system architecture, and a service plugin protocol for the MQTT-based IIoT application environment.

• Smart Media Journal
• /
• v.6 no.2
• /
• pp.42-49
• /
• 2017

It is important to realize automation services by communicating in IoT with humans, objects & objects, and forming a common network. People used web like the most powerful network way to sharing things and communication. Therefore the efficiency method communication between each device and the web in IoT could be different from ones. The best method for high quality software product in web applications is software reuse ; Modules, classes, patterns, frameworks, and business components are reusable elements of various perspectives. Components is plugged with others through well-defined interfaces, which can overcome the operation and complexity of application development. A web-based distributed environment for IoT applications is a standard architecture use information collected from various devices for developing and using applications. For that reason, the network management which manages the constituent resources for the best service control in IoT application is required as a sub-layer support service in most applications as well as individual applications. In this paper, we measure to develop a network management system based not only by components but on heterogeneous internetworks. For procedure this, we clarify a component architecture for classifying and classify also the component needed in the IOT and network domain or order the type of real network management system.

• KIPS Transactions on Software and Data Engineering
• /
• v.4 no.3
• /
• pp.99-110
• /
• 2015

Internet-of-Things(IoT) is the computing paradigm converged with different technologies, where diverse devices are connected via the wireless network, acquire environmental information from their equipped sensors, and actuated. IoT applications typically provide smart services to users by interacting with multiple devices connected to the network and are designed by integrating multiple technologies such as sensor network, communication technologies, and software engineering. Moreover, since the concept of IoT has been introduced recently, most of the researches are in the beginning step, which is too early to be practically applied. Due to these facts, developing IoT application results in unconventional technical challenges which have not been observed in typical software applications. And, it is not straightforward to apply conventional project guidelines to IoT application development projects. Hence, there can be many difficulties to successfully complete the projects. Therefore, for successful completion of the projects, we analyze technical challenges occurring in all phases of the project lifecycle, i.e. project preparation stage and development stage. And, we propose the effective solutions to overcome the issues. To verify identified issues and presented solutions, we present the result of applying the solutions to an IoT application development. Through the case study, we evaluate how reasonable the unconventional technical issues are generated and analyze effectiveness of applying the solutions to the application.

• Journal of electromagnetic engineering and science
• /
• v.16 no.4
• /
• pp.214-218
• /
• 2016

In this paper, we present an ambient light backscatter communication design that enables Internet of Things (IoT) devices to communicate through the backscattering ambient light emitted from lighting infrastructure or sunlight. The device can selectively modulate ambient light by switching a liquid crystal display (LCD) shutter located on its surface, so that a nearby smart device, which includes a photodiode or a camera, can demodulate this backscattered light information. To verify the practicality of the proposed concept, we design an IoT device equipped with a commercial LCD shutter and a microcontroller. Our device produces ambient light backscattered data at a speed of 100 bps, and these data are successfully decoded by a commercial photodiode module 10 cm away from the IoT device. We believe that our ambient light backscatter communication design is appropriate for implementation in various IoT applications.