• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.5
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• pp.1798-1813
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• 2021

This paper proposes a positive experience design approach for Internet of Things (IoT) intelligent products to improve users' subjective well-being in the fields of artificial intelligence and big data. First, the authors selected six target users and taking the Xiaomi IoT intelligent products for the research objects and conducted a thorough observation on how the target users used IoT intelligent products in their own homes over two weeks via a home-visiting interview, group diary, and focus group. Second, they constructed an individual activities table for the participants' IoT intelligent product experience using a hierarchical task analysis (HTA). Third, two researchers sorted out the sub-tasks of happiness in the HTA table. Finally, the authors found the positive experience design approach of IoT intelligent products. The positive experience design approach of IoT intelligent products is proposed from focusing on the personal pleasure experience to individual life meaningful design and group social relationship design, including individual pleasure experience, personal goal realization, group needs satisfaction and the harmony of group relations. The paper uses the two design examples of an interactive kettle and a harmonious chair to further discuss the feasibility of the design approach. In the era of big data, it is helpful for designers to use this design approach to improve the users' sense of sustainable pleasure, achievement perception of their future goal realization, and the well-being of the group's social relationships.

• Electronics and Telecommunications Trends
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• v.34 no.1
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• pp.1-12
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• 2019

The role of Internet of Things (IoT) has been evolving from connectivity to intelligent and autonomous functions. The increase in the number of connected things and the volume of data has revealed the limit of cloud-based intelligent IoT. Meanwhile, the development of microprocessors for the IoT has enabled their intelligent decision making and reactions without the intervention of the cloud; this phase is referred to as the "autonomous IoT era." However, intelligence is not the only function of the IoT. When a cyber physical system (CPS) is running on the cloud, the real-time synchronization between the real and virtual worlds cannot be guaranteed. If a CPS is running on the IoT, both the worlds can be synchronized closely enough for a zero- time gap, i.e., achieving the goals of autonomous IoT. ETRI implements intelligence into the role of IoT and collaborates their decision making and reactions without the intervention of humans. Then, we focus on the development of a new IoT computing paradigm that enables human-like discussions.

• Smart Media Journal
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• v.13 no.1
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• pp.60-66
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• 2024

The Internet of Things, which began by connecting sensors through a network, is developing into an intelligent IoT by combining it with artificial intelligence technology. Elevators are essential for high-rise buildings in the city, and elevators move from floor to floor and perform the functions of transporting goods and moving users. It is necessary to provide safe and convenient services for elevator users in high-rise buildings or special environments (hospitals, etc.). In an environment where rapid patient transportation is important, such as large hospitals, there is a problem that hospital staff and the general public often use the elevator for patients. In particular, when moving patients where golden time is important, the waiting time to board the elevator is a major hindrance. In order to solve this problem, this study proposes an intelligent IoT system for elevator calling using smartphone Bluetooth. First, we experimented with the elevator calling IoT system using smartphone Bluetooth, and as a result of the experiment, it was confirmed that it can authenticate elevator users and reduce unnecessary waiting time for boarding. In addition, we propose an intelligent IoT system that connects with intelligent IoT.

• Journal of Convergence for Information Technology
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• v.11 no.3
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• pp.140-146
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• 2021

As the environment using intelligent IoT devices increases, various studies are underway to ensure the integrity of information sent and received from intelligent IoT devices. However, all IoT information generated in heterogeneous environments is not fully provided with reliable protocols and services. In this paper, we propose an intelligent-based multi-blockchain model that can extract only critical information among various information processed by intelligent IoT devices. In the proposed model, blockchain is used to ensure the integrity of IoT information sent and received from IoT devices. The proposed model uses the correlation index of the collected information to trust a large number of IoT information to extract only the information with a high correlation index and bind it with blockchain. This is because the collected information can be extended to the n-tier structure as well as guaranteed reliability. Furthermore, since the proposed model can give weight information to the collection information based on blockchain, similar information can be selected (or bound) according to priority. The proposed model is able to extend the collection information to the n-layer structure while maintaining the data processing cost processed in real time regardless of the number of IoT devices.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.8
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• pp.1494-1502
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• 2016

With the increasing availability of medical sensors and Internet of Things(IoT) devices for personal use, considering the interaction with users, it is planned to add intelligent function design to the fashionable jewelry, and develop composite multi-function intelligent jewelry through sensors identification. By means of IoT technology, while possessing communication function of intelligent jewelry, the function of intelligent jewelry can be expanded to the linkage network. In order to rapidly manage the mass data produced by intelligent jewelry sensors based on IoT, an intelligent jewelry system for health management is designed and an ontology model of intelligent jewelry system based on IoT is worked out. After the state of the services through the smart phone application is shown. The application provides a personalized service to the user and to determine the risk to show the guide lines according to the disease.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.11
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• pp.2119-2124
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• 2016

The Internet of things (IoT) needs to be an event-driven approach for efficient related time response and processing. The growth of mobile devices in Internet of Things (IoT) leads to a number of intelligent buildings related IoT applications. For instance, home automation controlling system uses client system such web apps on smartphone or web service to access the home server by sending control commands. The gateway based RESTful technology responsible for handling clients'requests attests an internet latency in case a large number of clients' requests submit toward the gateway increases. In this paper, we propose the design tasks of the IoT gateway for handling concurrency events. The gateway based event-driven architecture is designed for building IoT gateway using node.js on one side and communication protocol based message-oriented middleware known as XMPP to handle communications of intelligent building control devices connected to the gateway through a centralized hub.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.83-90
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• 2022

Traditional Cloud Computing would be unable to safely host IoT data due to its high latency as the number of IoT sensors and physical devices accommodated on the Internet grows by the day. Because of the difficulty of processing all IoT large data on Cloud facilities, there hasn't been enough research done on automating the security of all components in the IoT-Cloud ecosystem that deal with big data and real-time jobs. It's difficult, for example, to build an automatic, secure data transfer from the IoT layer to the cloud layer, which incorporates a large number of scattered devices. Addressing this issue this article presents an intelligent algorithm that deals with enhancing security aspects in IoT cloud ecosystem using butterfly optimization algorithm.

• Journal of the Korea Convergence Society
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• v.8 no.11
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• pp.37-42
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• 2017

Over the next decade, there are estimated to be 250 billion IoT devices in the future, and a variety of new services and device markets are expected to be created via a new network connection. However, it is difficult to accommodate various sensors and IoT devices, such as product and installation environments, for existing IP/SIP/IMS cameras and video door phone. Additionally, recently, sensors and actuators that can accommodate IoT technology and standards are continually updated. In addition, this paper has developed an SIP/IMS intelligent gateway to flexibly accommodate IoT related equipments and to interface with ZigBee/Z-Wave/NFC endpoints in addition to the gateway basic functions. This intelligent gateway will contribute to the development of the IMS system to replace the VoIP system with the IMS equipment due to the growth of the IMS market.

• Journal of Korean Society of Rural Planning
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• v.21 no.4
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• pp.177-186
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• 2015

The main objective of this study was to assess the applicability of IoT (Internet of Things)-based flood management under climate change by developing intelligent water level monitoring platform based on IoT. In this study, Arduino Uno was selected as the development board, which is an open-source electronic platform. Arduino Uno was designed to connect the ultrasonic sensor, temperature sensor, and data logger shield for implementing IoT. Arduino IDE (Integrated Development Environment) was selected as the Arduino software and used to develop the intelligent algorithm to measure and calibrate the real-time water level automatically. The intelligent water level monitoring platform consists of water level measurement, temperature calibration, data calibration, stage-discharge relationship, and data logger algorithms. Water level measurement and temperature calibration algorithm corrected the bias inherent in the ultrasonic sensor. Data calibration algorithm analyzed and corrected the outliers during the measurement process. The verification of the intelligent water level measurement algorithm was performed by comparing water levels using the tape and ultrasonic sensor, which was generated by measuring water levels at regular intervals up to the maximum level. The statistics of the slope of the regression line and $R^2$ were 1.00 and 0.99, respectively which were considered acceptable. The error was 0.0575 cm. The verification of data calibration algorithm was performed by analyzing water levels containing all error codes in a time series graph. The intelligent platform developed in this study may contribute to the public IoT service, which is applicable to intelligent flood management under climate change.

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