본문 바로가기
KERD
논문KCI 등재

인공지능 기반 첨단물류기술의 진화경로 및 신흥트렌드

The Evolution Path and Emerging Trends of AI-Based Advanced Logistics Technologies

김지대|김호용
한국물류과학기술학회 (The Society of Logistics Science and Technology)|2024.12|물류과학기술연구 (Journal of Logistics Science & Technology)|제5권 제4호|pp. 87-106|DOI 10.23178/jlst.5.4.202412.006

0

조회

0

다운로드

0

인용

0

참고문헌

키워드

AI인공지능Patent AnalysisBERTopic물류기술Logistics Technology특허분석
주제분류과학기술학

초록

본 연구는 4차 산업혁명의 핵심동력인 인공지능과 융합된 첨단물류기술의 과거와 현재, 그리고 미래의 유망한 기술 분야를 탐색하고자 수행되었다. 2004년부터 2023년까지 미국특허청(USPTO)에 출원되어 현재 등록된 특허 6,000건을 수집 및 추출하였다. 분석 방법으로 연도별 출원 동향, 국가 분포, 주요 출원인 및 IPC코드의 탐색적 분석, 특허명 텍스트 빈도 분석, 딥러닝 기반의 BERTopic을 활용하였다. 분석 결과, 인공지능 기반 물류 특허 수는 꾸준한 증가세가 나타나고 있었다. 또한, 특허가 가장 많이 출원된 토픽 분야로는 ‘RFID 기반의 탐지 및 모니터링’으로 나타났다. 특히, ‘잠금 및 보안’, ‘자율주행’, ‘로봇’ 토픽이 최근 출원 활동성이 높은 신흥트렌드임을 확인하였다. 본 연구 결과가 기업의 R&D 활동과 물류기술 정책 입안자의 결정을 지원하기 위한 정보를 제공할 수 있을 것이라 기대된다.

Abstract

This study aims to explore the past, present, and future promising technological areas of advanced logistics technology integrated with artificial intelligence, a key driver of the Fourth Industrial Revolution. A total of 6,000 patents filed and currently registered with the United States Patent and Trademark Office (USPTO) from 2004 to 2023 were collected and analyzed. The analysis methods included exploratory analysis of annual filing trends, country distribution, major applicants, and IPC codes, text frequency analysis of patent titles, and the use of the deep learning-based BERTopic model. The results showed a consistent increase in the number of AI-based logistics patents. The topic with the highest number of patent filings was identified as “RFID-based detection and monitoring.” Additionally, emerging trends with recent high filing activity were found in the areas of "locking and security," "autonomous driving," and "robotics." The findings of this study are expected to provide valuable insights to support R&D activities of companies and decision-making by logistics technology policymakers.

참고문헌 (46)

  1. Albalawi, R., "Using Topic Modeling Methods for Short-Text Data : A Comparative Analysis", Frontiers in Artificial Intelligence, 3(42) (2020)
  2. Atzeni, D., "A Systematic Review of Wi-Fi and Machine Learning Integration with Topic Modeling Techniques", Sensors, 22(13), pp.4925~ (2022)
  3. Baek, S., "Analysis of Artificial Intelligence’s Technology Innovation and Diffusion Pattern: Focusing on USPTO Patent Data", The Journal of the Korea Contents Association, 20(4), pp.86~98 (2020)
  4. Bamakan, S., "Blockchain technology forecasting by patent analytics and text mining", Research and Applications, 2(2) (2021)
  5. Bubela, T., "Patent landscaping for life sciences innovation: Toward consistent and transparent practices", Nature Biotechnology, 31(3), pp.202~206 (2013)
  6. Chauhan, C., "Linking circular economy and digitalisation technologies: A systematic literature review of past achievements and future promises", Technological Forecasting and Social Change, 177 (2022)
  7. Cheong, M., "HDBSCAN-based Clutter Removal of An Active Sonar under Multipath Environment", Journal of The Institute of Electronics and Information Engineers, 61(8), pp.751~760 (2024)
  8. Choi, S., "Analyzing the Technological Competitiveness of Innovative Industries Using Patent Data: Focusing on AI Speakers", Korea Society of Innovation, 18(2), pp.55~75 (2023)
  9. Devlin, J., "BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding", Association for Computational Linguistics, 1, pp.4171~4186 (2019)
  10. Dwivedi, Y. K., "Evolution of artificial intelligence research in Technological Forecasting and Social Change: Research topics, trends, and future directions", Technological Forecasting and Social Change, 192 (2023)
  11. Elragal. A., "Theory-driven or process-driven prediction? Epistemological challenges of big data analytics", Journal of Big Data, 4 (2017)
  12. Gallagher, R. J., "Anchored correlation explanation: topic modeling with minimal domain knowledge", Transactions of the Association for Computational Linguistics, 5, pp.529~542 (2017)
  13. Garsson, R. S., "Strategies for Post-Grant Reviews and Other Proceedings for Challenging an Issued Patent", Nanotechnology Reviews, 1(4), pp.343~350 (2012)
  14. Gonzalez, G., "Prediction of Promising Vacant Logistics Technology using Patent Data Analytics in Latin America", Journal of the Korean Society of Supply Chain Management, 23(1), pp.11~19 (2023)
  15. Grootendorst, M., "BERTopic: Neural topic modeling with a class-based TF-IDF procedure" (2022)
  16. Holand. Ø., "’The Times They Are A-Changin’ – research trends and perspectives of reindeer pastoralism – A review using text mining and topic modelling", Land Use Policy, 136 (2024)
  17. Hong, L., "Empirical study of topic modeling in Twitter", Proceedings of the First Workshop on Social Media Analytics, pp.80~88 (2010)
  18. Hwang, H., "A Study on the Trend of Logistics Automation Based on Patent IPC Network Analysis and Word2Vec", Innovation Studies, 14(4), pp.235~263 (2019)
  19. Hwang, I. B., "The study for logistics technology trends by the method of patent network analysis and Word2Vec", Journal of the Korea Academia-Industrial cooperation Society, 23(9), pp.560~568 (2022)
  20. Hwang, I., "The study for logistics technology trends by the method of patent network analysis and Word2Vec", Journal of the Korea Academia-Industrial, 23(9), pp.560~568 (2022)
  21. Jung, J., "Analysis of AI Technology Application Paradigms in the Field of Secondary Batteries : A Patent Data Text Mining Study Using BERTopic Model", Journal of Korea Technology Innovation Society, 27(5), pp.891~912 (2024)
  22. Kang, W., "A Matrix Factorization-based Recommendation Approach with SBERT Embedding", Journal of Korean Institute of Information Technology, 21(11), pp.203~211 (2023)
  23. "A Brief History of Deep Learning" (2022)[URL]
  24. Kim, H., "Analysis of Research Trends Related to Jeju Region Based on LDA Topic Modeling", Journal of Jeju Studies, 61, pp.291~314 (2024)
  25. Kim, T. M., "Analysis and Forecast of Patent Trends in Unmanned Delivery Robot Technology : Focusing on Last-Mile Delivery Technology", Korea Logistics Review, 33(3), pp.30~42 (2023)
  26. Kim, Y., "Content-based Korean journal recommendation system using Sentence BERT", Journal of Intelligence and Information Systems, 29(3), pp.37~55 (2023)
  27. Kim, Y., "Extracting Urban Areas of Interest Using HDBSCAN Clustering Method", Journal of the Korean Cartographic Association, 23(1), pp.67~77 (2023)
  28. "KIPO" (2024)[URL]
  29. Kwak, H., "Competitiveness Analysis for Artificial Intelligence Technology through Patent Analysis", The Journal of Information Systems, 28(3), pp.141~158 (2019)
  30. Lee, H., "Forecast of Promising Technology on Last Mile Logistics by Analyzing the Patent Information", Korean Journal of Logistics, 29(2), pp.43~56 (2021)
  31. Lee, J., "A study on the technological development path of the AI semiconductor industry and the catch-up chance for latecomers : Focusing on technical patent analysis as the view of the technological life cycle", Journal of Korea Technology Innovation Society, 17(3), pp.113~133 (2022)
  32. Lee, K., "A Study on the Trends of Technology Development Related to Smart Factory Security : Based on Patent Analysis", The Korean Association for Industrial Security, 11(3), pp.49~71 (2021)
  33. Lee, W., "A Technology Landscape of Artificial Intelligence : Technological Structure and Firms’ Competitive Advantages", Journal of Korea Technology Innovation Society, 22(3), pp.340~361 (2019)
  34. Liu, Y., "Technology status tracing and trends in construction robotics : A patent analysis", World Patent Information, 76 (2024)
  35. Maji, I. K., "Regulatory role, clean logistics technology and environmental sustainability", Social Sciences & Humanities Open, 9 (2024)
  36. "The Myth of the 18-Month Delay in Publishing Patent Applications" (2015)[URL]
  37. Park, C., "Logistics Fulfillment Technology Analysis using Patent Information : Focusing on Coupang’s Patents", Korea Logistics Review, 32(1), pp.93~104 (2022)
  38. Park, Y. G., "The effect of technology innovation on the corporate value in logistics and distribution industry : based on the patent claims and citation", Journal of Distribution and Management Research, 21(3), pp.57~68 (2018)
  39. "Global Logistics Market Report and Forecast 2024-2032" (2023)[URL]
  40. Righi, R., "The AI techno-economic complex System : Worldwide landscape, thematic subdomains and technological collaborations", Telecommunications Policy, 44(6) (2020)
  41. Shim, M., "Analysis of Research Trends on the Domestic Metaverse using Topic Modeling : Focusing on Research from 2007 to 2022", Journal of Digital Contents Society, 23(12), pp.2457~2468 (2022)
  42. Shin, M., "A study on digital technology and smartization level in the logistics industry", Journal of Transport Research, 29(1), pp.43~61 (2022)
  43. Shin, M., "A study on digital technology and smartization level in the logistics industry", Journal of Transport Research, 29(1), pp.43~61 (2022)
  44. Wang. Y., "Exploring topic models to discern cyber threats on Twitter : A case study on Log4Shell", Intelligent Systems with Applications, 20 (2023)
  45. Wen. Z., "Inferring global-scale temporal latent topics from news reports to predict public health interventions for COVID-19", Patterns, 3 (2022)
  46. Yoon, H., "A comparative study on Technology competitiveness of Global AI Companies using patent and paper portfolio analysis", Journal of Korea Technology Innovation Society, 26(6), pp.817~841 (2023)

관련 논문AI추천

특허 분석을 이용한 글로벌 스마트 물류 트렌드 분석: 국내 물류 산업 발전을 중심으로류슬기, 박민영, 송영철, 윤병운, 이다예한국산업경영시스템학회 · 한국산업경영시스템학회지2024 · 제47권 제3호특허 IPC Network 분석 및 Word2Vec 기반 물류 자동화 기술동향에 관한 연구송상화, 황현철한국혁신학회 · 한국혁신학회지2019 · 제14권 제4호특허정보 빅데이터 분석을 통한 라스트마일 물류 유망기술 도출이현, 권구포, 유지원, 이철웅한국로지스틱스학회 · 로지스틱스연구2021 · 제29권 제2호토픽 모델링을 활용한 물류 분야 로봇 활용 관련 연구 이슈와 동향 분석김경아, 정호상한국로지스틱스학회 · 로지스틱스연구2023 · 제31권 제2호국내외 특허데이터 기반의 인공지능분야 기술동향 분석이주연, 정명석, 정소희한국디지털정책학회 · 디지털융복합연구2018 · 제16권 제6호인공지능 관련 지식재산권 연구 동향 분석김태훈, 배성희한국지식재산연구원 · 지식재산연구2024 · 제19권 제4호

이 간행물의 다른 논문 (6건)

파레트가 다단 적재된 실내 환경에서의 지게차 포킹 자동화 알고리즘이기백, 이석, 우효원, 이순교, 이창현, 박유현, 박주형pp. 1-15국내 물류 기업의 인수합병(M&A) 동기에 관한 연구박기화pp. 16-32머신러닝을 활용한 구간별 극점 기반 판매량 예측임현우, 정영철pp. 33-48컨베이어 시스템에서 불균등한 입출력(I/O) 흐름의 균형 조정을 통한 시스템 운영 효율성 향상채준재, 허진혁pp. 49-61다중 에이전트 강화 학습을 이용한 트랜스포터 혼잡 회피 경로 계획 최적화윤성재pp. 62-86
원문 보기