• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.3
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• pp.291-300
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• 2016

The emergence of smart devices and IoT leads to the appearance of O2O service to blur the difference between online and offline. As online services' merits were added to the offline market, it caused a change in the dynamics of the offline industry, which means the offline-space's digitization. Unlike these changing aspects of the offline market, exhibition industry grows steadily in the industry, however it is also possible to create a new value added by combining O2O service. We conducted a survey targeting 20 spectators in '2015 Seoul Design Festival' at COEX. The survey was used to analysis of the spatial structure and generate the dataset for machine learning. We identified problems with the analysis study of the existing spatial structure, and based on this investigation we propose a new method for analyzing a spatial structure. Also by processing a machine learning technique based on the generated dataset, we propose a novel evaluation model of exhibition-space cells for O2O service layout.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.2
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• pp.81-88
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• 2016

Machine-to-Machine (M2M) communication provides each component (machine) with access to Internet, evolving into the IoT technology. IoT is a trend where numbers of devices provide the communication service, using the Internet protocol. As spreading the concept of IoT(Internet of Things), various objects become home information sources. According to the wide spread of various devices, it is difficult to access data on the devices with unified manners. Under this environment, security is a critical element to create various types of application and service. In this paper propose the inter-device authentication and Centralized Remote Security Provisioning framework in Open M2M environment. The results of previous studies in this task is carried out by protecting it with the latest information on M2M / IoT and designed to provide the ultimate goal of future M2M / IoT optimized platform that can be integrated M2M / IoT service security and security model presents the information.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.6
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• pp.827-837
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• 2017

Since the area of smart home has been attracting attention, researches have been conducted to control syntagmatically various electronic products with a single remote controller. Previous researches have developed a dedicated controller or an application that acts as a remote controller and controls electronic products by configuring control screen for each product. However, these approaches are not suitable for controlling various electronic products that should be controlled by configuring separate control screens for each product. In this paper, we propose a web-based remote control platform. We define universal user interfaces applicable to various devices by categorizing user interactions of electronic goods and implement them as APIs. By applying the APIs to IPTV and car navigation devices we show that it is possible to control them through only a web browser. We also propose a method to group multiple control requests in order to efficiently handle consecutive control requests and show the improved response time and data usage.

• Convergence Security Journal
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• v.22 no.2
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• pp.27-42
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• 2022

In the era of the Fourth Industrial Revolution, digital transformation to increase the effectiveness of industry is becoming more important to achieving the goal of industrial innovation. The digital new deal and smart defense are required for digital transformation and utilize artificial intelligence, big data analysis technology, and the Internet of Things. These changes can innovate the industrial fields of national defense, society, and health with new intelligent services by continuously expanding cyberspace. As a result, work productivity, efficiency, convenience, and industrial safety will be strengthened. However, the threat of cyber-attack will also continue to increase due to expansion of the new domain of digital transformation. This paper presents the risk scenarios of cyber-attack threats in the Fourth Industrial Revolution. Further, we propose a preemptive intrusion response model to bolster the complex security environment of the future, which is one of the fundamental alternatives to solving problems relating to cyber-attack. The proposed model can be used as prior research on cyber security strategy and technology development for preemptive response to cyber threats in the future society.

• The Journal of Bigdata
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• v.8 no.1
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• pp.1-10
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• 2023

This paper presents the design process of an agricultural data sharing platform intended to address major challenges faced by the domestic agricultural industry. The platform was designed with a user interface that prioritizes user requirements for ease of use and offers various analysis techniques to provide growth prediction for field environment, growth, management, and control data. Additionally, the platform supports File to DB and DB to DB linkage methods to ensure seamless linkage between the platform and farmhouses. The UI design process utilized HTML/CSS-based languages, JavaScript, and React to provide a comprehensive user experience from platform login to data upload, analysis, and detailed inquiry visualization. The study is expected to contribute to the development of Korean smart farm models and provide reliable data sets to agricultural industry sites and researchers.

• The Journal of Bigdata
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• v.8 no.2
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• pp.141-148
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• 2023

Recent advancements in the integration of satellite technology and the Internet of Things (IoT) have led to the development of a sophisticated network ecosystem, capable of generating and utilizing vast amounts of big data across various sectors. However, this integrated network faces significant security challenges, primarily due to constraints like limited latency, low power requirements, and the incorporation of diverse heterogeneous devices. Addressing these security concerns, this paper explores the construction of a satellite-IoT network through the application of Software Defined Networking (SDN). While SDN offers numerous benefits, it also inherits certain inherent security vulnerabilities. To mitigate these issues, we propose a novel approach that incorporates blockchain technology within the SDN framework. This blockchain-based SDN environment enhances security through a distributed controller system, which also facilitates the authentication of IoT terminals and nodes. Our paper details the implementation plan for this system and discusses its validation through a series of tests. Looking forward, we aim to expand our research to include the convergence of artificial intelligence with satellite-IoT devices, exploring new avenues for leveraging the potential of big data in this context.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.7
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• pp.1968-1985
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• 2024

At present, the world is witnessing a rapid change in all the fields of human civilization business interests and goals of all the sectors are changing very fast. Global changes are taking place quickly in all fields - manufacturing, service, agriculture, and external sectors. There are plenty of hurdles in the emerging technologies in agriculture in the modern days. While adopting such technologies as transparency and trust issues among stakeholders, there arises a pressurized necessity on food suppliers because it has to create sustainable systems not only addressing demand-supply disparities but also ensuring food authenticity. Recent studies have attempted to explore the potential of technologies like blockchain and practices for smart and sustainable agriculture. Besides, this well-researched work investigates how a scientific cum technological blockchain architecture addresses supply chain challenges in Precision Agriculture to take up challenges related to transparency traceability, and security. A robust registration phase, efficient authentication mechanisms, and optimized data management strategies are the key components of the proposed architecture. Through secured key exchange mechanisms and encryption techniques, client's identities are verified with inevitable complexity. The confluence of IoT and blockchain technologies that set up modern farms amplify control within supply chain networks. The practical manifestation of the researchers' novel blockchain architecture that has been executed on the Hyperledger network, exposes a clear validation using corroboration of concept. Through exhaustive experimental analyses that encompass, transaction confirmation time and scalability metrics, the proposed architecture not only demonstrates efficiency but also underscores its usability to meet the demands of contemporary Precision Agriculture systems. However, the scholarly paper based upon a comprehensive overview resolves a solution as a fruitful and impactful contribution to blockchain applications in agriculture supply chains.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.203-219
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• 2011

Previously common users just want to watch the video contents without any specific requirements or purposes. However, in today's life while watching video user attempts to know and discover more about things that appear on the video. Therefore, the requirements for finding multimedia or browsing information of objects that users want, are spreading with the increasing use of multimedia such as videos which are not only available on the internet-capable devices such as computers but also on smart TV and smart phone. In order to meet the users. requirements, labor-intensive annotation of objects in video contents is inevitable. For this reason, many researchers have actively studied about methods of annotating the object that appear on the video. In keyword-based annotation related information of the object that appeared on the video content is immediately added and annotation data including all related information about the object must be individually managed. Users will have to directly input all related information to the object. Consequently, when a user browses for information that related to the object, user can only find and get limited resources that solely exists in annotated data. Also, in order to place annotation for objects user's huge workload is required. To cope with reducing user's workload and to minimize the work involved in annotation, in existing object-based annotation automatic annotation is being attempted using computer vision techniques like object detection, recognition and tracking. By using such computer vision techniques a wide variety of objects that appears on the video content must be all detected and recognized. But until now it is still a problem facing some difficulties which have to deal with automated annotation. To overcome these difficulties, we propose a system which consists of two modules. The first module is the annotation module that enables many annotators to collaboratively annotate the objects in the video content in order to access the semantic data using Linked Data. Annotation data managed by annotation server is represented using ontology so that the information can easily be shared and extended. Since annotation data does not include all the relevant information of the object, existing objects in Linked Data and objects that appear in the video content simply connect with each other to get all the related information of the object. In other words, annotation data which contains only URI and metadata like position, time and size are stored on the annotation sever. So when user needs other related information about the object, all of that information is retrieved from Linked Data through its relevant URI. The second module enables viewers to browse interesting information about the object using annotation data which is collaboratively generated by many users while watching video. With this system, through simple user interaction the query is automatically generated and all the related information is retrieved from Linked Data and finally all the additional information of the object is offered to the user. With this study, in the future of Semantic Web environment our proposed system is expected to establish a better video content service environment by offering users relevant information about the objects that appear on the screen of any internet-capable devices such as PC, smart TV or smart phone.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.131-145
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• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.

• Economic and Environmental Geology
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• v.53 no.5
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• pp.609-617
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• 2020

After introducing the industry 4.0 policy, Korean government announced 'Digital New Deal' and 'Green New Deal' as 'Korean New Deal' in 2020. We analyzed Korea Institute of Geoscience and Mineral Resources (KIGAM)'s research projects related to that policy and conducted markets analysis focused on Digital Twin and environmental monitoring technologies. Regarding 'Data Dam' policy, we suggested the digital geo-contents with Augmented Reality (AR) & Virtual Reality (VR) and the public geo-data collection & sharing system. It is necessary to expand and support the smart mining and digital oil fields research for '5th generation mobile communication (5G) and artificial intelligence (AI) convergence into all industries' policy. Korean government is suggesting downtown 3D maps for 'Digital Twin' policy. KIGAM can provide 3D geological maps and Internet of Things (IoT) systems for social overhead capital (SOC) management. 'Green New Deal' proposed developing technologies for green industries including resource circulation, Carbon Capture Utilization and Storage (CCUS), and electric & hydrogen vehicles. KIGAM has carried out related research projects and currently conducts research on domestic energy storage minerals. Oil and gas industries are presented as representative applications of digital twin. Many progress is made in mining automation and digital mapping and Digital Twin Earth (DTE) is a emerging research subject. The emerging research subjects are deeply related to data analysis, simulation, AI, and the IoT, therefore KIGAM should collaborate with sensors and computing software & system companies.