• Title/Summary/Keyword: Transition Platform

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Operational Ship Monitoring Based on Multi-platforms (Satellite, UAV, HF Radar, AIS) (다중 플랫폼(위성, 무인기, AIS, HF 레이더)에 기반한 시나리오별 선박탐지 모니터링)

  • Kim, Sang-Wan;Kim, Donghan;Lee, Yoon-Kyung;Lee, Impyeong;Lee, Sangho;Kim, Junghoon;Kim, Keunyong;Ryu, Joo-Hyung
    • Korean Journal of Remote Sensing
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    • v.36 no.2_2
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    • pp.379-399
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    • 2020
  • The detection of illegal ship is one of the key factors in building a marine surveillance system. Effective marine surveillance requires the means for continuous monitoring over a wide area. In this study, the possibility of ship detection monitoring based on satellite SAR, HF radar, UAV and AIS integration was investigated. Considering the characteristics of time and spatial resolution for each platform, the ship monitoring scenario consisted of a regular surveillance system using HFR data and AIS data, and an event monitoring system using satellites and UAVs. The regular surveillance system still has limitations in detecting a small ship and accuracy due to the low spatial resolution of HF radar data. However, the event monitoring system using satellite SAR data effectively detects illegal ships using AIS data, and the ship speed and heading direction estimated from SAR images or ship tracking information using HF radar data can be used as the main information for the transition to UAV monitoring. For the validation of monitoring scenario, a comprehensive field experiment was conducted from June 25 to June 26, 2019, at the west side of Hongwon Port in Seocheon. KOMPSAT-5 SAR images, UAV data, HF radar data and AIS data were successfully collected and analyzed by applying each developed algorithm. The developed system will be the basis for the regular and event ship monitoring scenarios as well as the visualization of data and analysis results collected from multiple platforms.

Beyond Platforms to Ecosystems: Research on the Metaverse Industry Ecosystem Utilizing Information Ecology Theory (플랫폼을 넘어 생태계로: Information Ecology Theory를 활용한 메타버스 산업 생태계연구 )

  • Seokyoung Shin;Jaiyeol Son
    • Information Systems Review
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    • v.25 no.4
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    • pp.131-159
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    • 2023
  • Recently, amidst the backdrop of the COVID-19 pandemic shifting towards an endemic phase, there has been a rise in discussions and debates about the future of the metaverse. Simultaneously, major metaverse platforms like Roblox have been launching services integrated with generative AI, and Apple's mixed reality hardware, Vision Pro, has been announced, creating new expectations for the metaverse. In this situation where the outlook for the metaverse is divided, it is crucial to diagnose the metaverse from an ecosystem perspective, examine its key ecological features, driving forces for development, and future possibilities for advancement. This study utilized Wang's (2021) Information Ecology Theory (IET) framework, which is representative of ecosystem research in the field of Information Systems (IS), to derive the Metaverse Industrial Ecosystem (MIE). The analysis revealed that the MIE consists of four main domains: Tech Landscape, Category Ecosystem, Metaverse Platform, and Product/Service Ecosystem. It was found that the MIE exhibits characteristics such as digital connectivity, the integration of real and virtual worlds, value creation capabilities, and value sharing (Web 3.0). Furthermore, the interactions among the domains within the MIE and the four characteristics of the ecosystem were identified as driving forces for the development of the MIE at an ecosystem level. Additionally, the development of the MIE at an ecosystem level was categorized into three distinct stages: Narrow Ecosystem, Expanded Ecosystem, and Everywhere Ecosystem. It is anticipated that future advancements in related technologies and industries, such as robotics, AI, and 6G, will promote the transition from the current Expanded Ecosystem level of the MIE to an Everywhere Ecosystem level, where the connection between the real and virtual worlds is pervasive. This study provides several implications. Firstly, it offers a foundational theory and analytical framework for ecosystem research, addressing a gap in previous metaverse studies. It also presents various research topics within the metaverse domain. Additionally, it establishes an academic foundation that integrates concept definition research and impact studies, which are key areas in metaverse research. Lastly, referring to the developmental stages and conditions proposed in this study, businesses and governments can explore future metaverse markets and related technologies. They can also consider diverse metaverse business strategies. These implications are expected to guide the exploration of the emerging metaverse market and facilitate the evaluation of various metaverse business strategies.

A Study on Factors Affecting BigData Acceptance Intention of Agricultural Enterprises (농업 관련 기업의 빅데이터 수용 의도에 미치는 영향요인 연구)

  • Ryu, GaHyun;Heo, Chul-Moo
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.17 no.1
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    • pp.157-175
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    • 2022
  • At this moment, a paradigm shift is taking place across all sectors of society for the transition movements to the digital economy. Various movements are taking place in the global agricultural industry to achieve innovative growth using big data which is a key resource of the 4th industrial revolution. Although the government is making various attempts to promote the use of big data, the movement of the agricultural industry as a key player in the use of big data, is still insufficient. Therefore, in this study, effects of performance expectations, effort expectations, social impact, facilitation conditions, based on the Unified Theory of Acceptance and Use of Technology(UTAUT), and innovation tendencies on the acceptance intention of big data were analyzed using the economic and practical benefits that can be obtained from the use of big data for agricultural-related companies as moderating variables. 333 questionnaires collected from agricultural-related companies were used for empirical analysis. The analysis results using SPSS v22.0 and Process macro v3.4 were found to have a significant positive (+) effect on the intention to accept big data by effort expectations, social impact, facilitation conditions, and innovation tendencies. However, it was found that the effect of performance expectations on acceptance intention was insignificant, with social impact having the greatest influence on acceptance intention and innovation tendency the least. Moderating effects of economic benefit and practical benefit between effort expectation and acceptance intention, moderating effect of practical benefit between social impact and acceptance intention, and moderating effect of economic benefit and practical benefit between facilitation condition and acceptance intention were found to be significant. On the other hand, it was found that economic benefits and practical benefits did not moderate the magnitude of the influence of performance expectations and innovation tendency on acceptance intention. These results suggest the following implications. First, in order to promote the use of big data by companies, the government needs to establish a policy to support the use of big data tailored to companies. Significant results can only be achieved when corporate members form a correct understanding and consensus on the use of big data. Second, it is necessary to establish and implement a platform specialized for agricultural data which can support standardized linkage between diverse agricultural big data, and support for a unified path for data access. Building such a platform will be able to advance the industry by forming an independent cooperative relationship between companies. Finally, the limitations of this study and follow-up tasks are presented.

Group storytelling with multi-storyteller in single person media game contents on Youtube - focused on viewer-participating contents in channel (유튜브 1인 게임 방송의 집단 스토리텔링 -<대도서관 TV(buzzbean11)> 채널의 시청자 참여형 콘텐츠를 중심으로)

  • Kil, Hye-Bin;Kim, So-Young
    • Journal of Popular Narrative
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    • v.27 no.2
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    • pp.107-142
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    • 2021
  • Emergence of new media platform had changed relationship between the broadcaster and the viewer, which used to form 'performer-audience' structure. This research has focused on the transition of 'streamer-viewer' role in single-media broadcasting, such as Youtube or Twitch, and identify how they progress group storytelling as a team. Walter Benjam and Leslie Marmon Silko's notion of 'story and storyteller' and Erving Goffman's 'social role theory' was used to define participants' role in new media broadcasting. channel, on Youtube, was selected and analyzed as example case. The domain of 'front stage' was broadened in recorded contents comparing to live streaming. The audience of live streaming is included to the front stage during the expansion. The role of streamer, game participant, and live stream contents viewer is also adjusted during the change, which leads to group-creation of the contents. Streamer plays a role of main-storyteller and suggest identity of the community. Game participants work as sub-storyteller, filling in the blank space in game storytelling and making it sophisticated. They also perform based on community's identity, which streamer has built in advance. Lastly, live steam viewers are intermittent sub-storyteller, which seldom add up the narrative. Though, their main role is to preserve identity of game broadcasting community by reacting according to community's identity. As a result, the game broadcasting narrative is developed by combining and adding up pieces of story made in different level and role of participants. The research redefine the role of viewer and storytelling method in new media, especially in single-person broadcasting. Considering the rapid shift in recent media and contents, a new approach to the streamer-veiwer role and group storytelling of this research can be one of the new method to analyze contents produced in new media, such as Youtube.