• 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 Korea Society of Digital Industry and Information Management
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• v.14 no.4
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• pp.27-33
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• 2018

The recent efforts in academia and industry represent a paradigm shift that will extend the IoT from the home environment so that it is interoperable with the Internet of Vehicles (IoV). IoV is a special kind of IoT. It allows to connect between vehicle and things located in infrastructure. Furthermore, IoV enable to create new intelligent services through collaboration with existing various services such as smart city and connected home. In this paper, we develop a service in order to realize IoV. To this end, we design a novel vehicle service platform which could automatical controlling the IoT device according to drivers' voice. To show practical usability of our proposed platform, we develop a prototype service could be call car-to-thing (C2T). We expect that our proposed platform could eventually contribute to realizing IoV.

• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.256-259
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• 2016

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 home server receives the command, then controls for instance the light system. 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. In the procedure of designing tasks, concurrency is best understood by employing multiple levels of abstraction. The way that is eminently to accomplish concurrency is to build an object-oriented environment with support for messages passing between concurrent objects. We also investigate the performance of event-driven architecture 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. The Node.JS is 40% faster than the traditional web server side features thread-based approach. The use of Node.js server-side handles a large number of clients' requests, then therefore, reduces delay in performing predefined actions automatically in intelligent building IoT environment.

• 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.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.8
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• pp.845-854
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• 2019

In IoT environment, an intelligent agent is an autonomous entity with computing power that interacts with various things for specific purposes without human intervention. Recently, as the development of Internet technology has increased the size of resources and services that intelligent agents can utilize, an environment where intelligent agents can collaborate with each other is needed. To effectively support these changes, a method is needed to provide workspaces where intelligent agents can form various groups and collaborate on them. In this paper, we present TSpace which is an Ethereum-based group workspace for effective collaboration among intelligent agents. In TSpace, intelligent agents in IoT environment can use group service based on the Ethereum blockchain through the developed CoAP/RESTful web service. TSpace also introduces a new mechanism for managing Ethereum wallets of agents accessing group services and for creating Ethereum transactions using them.

• Journal of Internet of Things and Convergence
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• v.1 no.1
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• pp.21-25
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• 2015

The Internet of Thing (IoT) will be a very important core technology to implement Intelligent Smart Home Network and it will take charge of an important role connected to Smart Phone, Cloud Computing in the Ubiquitous environment. In this paper, Internal Autonomous Regulation by human autonomic nervous system was studied and its core mechanism was applied to the design of IoT based Autonomous Regulation System for Intelligent Smart Home Network. We proposed an autonomous regulating mechanism in which the factors of Temperature, Humidity and Illumination are automatically adjusted as they communicate with the connected things.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.3
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• pp.419-424
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• 2015

The era of IoT in which all objects are intelligent and are connected to the Internet has been started. In order to establish and activate an IoT eco system, open services platform is very important. In this paper, we developed a BLE sensor module as a component of the open service platform based on the IoT and the open source hardware Blutooth4.0. To verify the functionality and performance of the developed BLE sensor module was built to evaluate the performance of the test environment.

• 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.

• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.1
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• pp.47-57
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• 2015

Recently, Internet of Things (IoT) have become popular for research and development in many areas. IoT makes a new intelligent network between things, between things and persons, and between persons themselves. Social network service technology is in its infancy, but, it has many benefits. Adjacent users in a social network tend to trust each other more than random pairs of users in the network. In this paper, we propose recommendation technique using social network in Internet of Things environment. We study previous researches about information recommendation, IoT, and social IoT. We proposed SIoT_P(Social IoT Prediction) using social relationships and item-based collaborative filtering. Also, we proposed SR(Social Relationship) using four social relationships (Ownership Object Relationship, Co-Location Object Relationship, Social Object Relationship, Parental Object Relationship). We describe a recommendation scenario using our proposed method.