包装中人工智能驱动的绿色创新:采用和扩散挑战的系统回顾

IF 4.3
Ye Ma, Nor Hidayati Zakaria, Basheer Al-Haimi, Chen Wu
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引用次数: 0

摘要

全球对环境保护的关注加剧了对可持续包装解决方案的需求。将人工智能(AI)融入绿色创新为应对这些挑战提供了一种变革性的方式。本研究采用以PRISMA 2020框架为指导的系统文献综述(SLR)来研究最近的人工智能包装创新。研究人员分析了2020年至2025年间发表的48篇同行评议文章。研究结果表明,机器学习、深度学习和通用人工智能应用是最常采用的技术。可生物降解的包装材料和智能包装系统代表了主要的可持续包装类型。人工智能应用主要集中在流程优化、智能包装监控、欺诈检测、计算机视觉和自然语言处理等方面。然而,广泛采用面临着诸如高成本、技术复杂性和监管不确定性等障碍。未来的趋势强调了可扩展技术、先进的人工智能模型、与循环经济的整合以及跨学科合作的重要性。本综述提供了一个结构化的框架,以指导学者、行业从业者和政策制定者采用人工智能驱动的绿色创新来实现可持续包装。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Artificial intelligence-driven green innovation in packaging: A systematic review of adoption and diffusion challenges
Global concern about environmental protection has intensified the demand for sustainable packaging solutions. Integrating artificial intelligence (AI) into green innovation offers a transformative way to address these challenges. This study applies a systematic literature review (SLR) guided by the PRISMA 2020 framework to examine recent AI-powered packaging innovations. Forty-eight peer-reviewed articles, published between 2020 and 2025, were analyzed. The findings show that Machine Learning, Deep Learning, and general AI applications are the most frequently adopted technologies. Biodegradable packaging materials and smart packaging systems represent the main sustainable packaging types. AI applications are concentrated in process optimization, smart packaging monitoring, fraud detection, computer vision, and natural language processing. However, widespread adoption faces obstacles such as high costs, technical complexity, and regulatory uncertainty. Future trends highlight the importance of scalable technologies, advanced AI models, integration with the circular economy, and interdisciplinary collaboration. This review provides a structured framework to guide academics, industry practitioners, and policymakers in adopting AI-driven green innovation for sustainable packaging.
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CiteScore
5.60
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