• Title/Summary/Keyword: AI Platform of Platforms

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A Study on Marine Application of Wireless Access in Vehicular Environment (WAVE) Communication Technology (차량용 무선통신기술(WAVE)의 해상적용에 관한 연구)

  • Kang, Won-Sik;Jeon, Soon-Bae;Kim, Young-Du
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.24 no.4
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    • pp.445-450
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    • 2018
  • AIS is the most important navigation equipment for the identification of other ships, etc. However, the AIS overload problem has been raised recently due to an increase in AIS equipped vessels. The government is planning to introduce the wireless LTE network at 100 km offshore as part of the SMART-Navigation project. Continuous development and dissemination of the services available through such platforms will be necessary to achieve major goals such as marine accident prevention and environmental protection. In this study, we applied a WAVE communication system, which could be the basis for the development of such services. As a result, reliable data transmission was confirmed for a range of communication of approx. 5 miles, although the service was limited to 1 km in road traffic. Therefore, it is expected that WAVE communication technology will be used to prevent marine accidents through such efforts as collision avoidance and the transfer of marine safety information between ships.

A Research on Image Metadata Extraction through YCrCb Color Model Analysis for Media Hyper-personalization Recommendation (미디어 초개인화 추천을 위한 YCrCb 컬러 모델 분석을 통한 영상의 메타데이터 추출에 대한 연구)

  • Park, Hyo-Gyeong;Yong, Sung-Jung;You, Yeon-Hwi;Moon, Il-Young
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.10a
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    • pp.277-280
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    • 2021
  • Recently as various contents are mass produced based on high accessibility, the media contents market is more active. Users want to find content that suits their taste, and each platform is competing for personalized recommendations for content. For an efficient recommendation system, high-quality metadata is required. Existing platforms take a method in which the user directly inputs the metadata of an image. This will waste time and money processing large amounts of data. In this paper, for media hyperpersonalization recommendation, keyframes are extracted based on the YCrCb color model of the video based on movie trailers, movie genres are distinguished through supervised learning of artificial intelligence and In the future, we would like to propose a utilization plan for generating metadata.

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Analysis of Success Cases of InsurTech and Digital Insurance Platform Based on Artificial Intelligence Technologies: Focused on Ping An Insurance Group Ltd. in China (인공지능 기술 기반 인슈어테크와 디지털보험플랫폼 성공사례 분석: 중국 평안보험그룹을 중심으로)

  • Lee, JaeWon;Oh, SangJin
    • Journal of Intelligence and Information Systems
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    • v.26 no.3
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    • pp.71-90
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    • 2020
  • Recently, the global insurance industry is rapidly developing digital transformation through the use of artificial intelligence technologies such as machine learning, natural language processing, and deep learning. As a result, more and more foreign insurers have achieved the success of artificial intelligence technology-based InsurTech and platform business, and Ping An Insurance Group Ltd., China's largest private company, is leading China's global fourth industrial revolution with remarkable achievements in InsurTech and Digital Platform as a result of its constant innovation, using 'finance and technology' and 'finance and ecosystem' as keywords for companies. In response, this study analyzed the InsurTech and platform business activities of Ping An Insurance Group Ltd. through the ser-M analysis model to provide strategic implications for revitalizing AI technology-based businesses of domestic insurers. The ser-M analysis model has been studied so that the vision and leadership of the CEO, the historical environment of the enterprise, the utilization of various resources, and the unique mechanism relationships can be interpreted in an integrated manner as a frame that can be interpreted in terms of the subject, environment, resource and mechanism. As a result of the case analysis, Ping An Insurance Group Ltd. has achieved cost reduction and customer service development by digitally innovating its entire business area such as sales, underwriting, claims, and loan service by utilizing core artificial intelligence technologies such as facial, voice, and facial expression recognition. In addition, "online data in China" and "the vast offline data and insights accumulated by the company" were combined with new technologies such as artificial intelligence and big data analysis to build a digital platform that integrates financial services and digital service businesses. Ping An Insurance Group Ltd. challenged constant innovation, and as of 2019, sales reached $155 billion, ranking seventh among all companies in the Global 2000 rankings selected by Forbes Magazine. Analyzing the background of the success of Ping An Insurance Group Ltd. from the perspective of ser-M, founder Mammingz quickly captured the development of digital technology, market competition and changes in population structure in the era of the fourth industrial revolution, and established a new vision and displayed an agile leadership of digital technology-focused. Based on the strong leadership led by the founder in response to environmental changes, the company has successfully led InsurTech and Platform Business through innovation of internal resources such as investment in artificial intelligence technology, securing excellent professionals, and strengthening big data capabilities, combining external absorption capabilities, and strategic alliances among various industries. Through this success story analysis of Ping An Insurance Group Ltd., the following implications can be given to domestic insurance companies that are preparing for digital transformation. First, CEOs of domestic companies also need to recognize the paradigm shift in industry due to the change in digital technology and quickly arm themselves with digital technology-oriented leadership to spearhead the digital transformation of enterprises. Second, the Korean government should urgently overhaul related laws and systems to further promote the use of data between different industries and provide drastic support such as deregulation, tax benefits and platform provision to help the domestic insurance industry secure global competitiveness. Third, Korean companies also need to make bolder investments in the development of artificial intelligence technology so that systematic securing of internal and external data, training of technical personnel, and patent applications can be expanded, and digital platforms should be quickly established so that diverse customer experiences can be integrated through learned artificial intelligence technology. Finally, since there may be limitations to generalization through a single case of an overseas insurance company, I hope that in the future, more extensive research will be conducted on various management strategies related to artificial intelligence technology by analyzing cases of multiple industries or multiple companies or conducting empirical research.