Eco-Bee：一种面向校园生态系统的个性化多模态代理，用于提升学生气候意识和可持续行为
Eco-Bee: A Personalised Multi-Modal Agent for Advancing Student Climate Awareness and Sustainable Behaviour in Campus Ecosystems
AI总结：
Eco-Bee通过整合大语言模型、行星边界框架（Eco-Score）和对话代理，为学生提供个性化反馈和行为激励，推动校园可持续发展。
摘要：
大学是城市生态系统的微缩体现，其消费模式在食品、交通、能源和产品使用方面高度集中。这些环境不仅对可持续性压力有显著贡献，也提供了大规模推进可持续教育和行为改变的独特机会。然而，大多数领域内的数字可持续性举措仍局限于碳计算，通常提供静态反馈，限制了持续行为改变的机会。为此，我们提出Eco-Bee，整合大语言模型、行星边界框架（作为Eco-Score）和一个连接个人选择与环境限制的对话代理。该系统专为即将形成终身习惯的学生设计，通过提供可操作见解、同伴基准和游戏化挑战来维持参与度，并推动向符合边界的生活方式取得可衡量的进步。在多个校园网络（n=52）的试点测试中，96%的学生支持校园范围内的推广，并报告了更清晰的日常行为如何影响地球限制的理解。通过将行星科学、行为强化和AI驱动的个性化整合到单一平台中，Eco-Bee为气候意识大学和未来的AI驱动可持续基础设施建立了可扩展的基础。
英文摘要：
Universities are microcosms of urban ecosystems, with concentrated consumption patterns in food, transport, energy, and product usage. These environments not only contribute substantially to sustainability pressures but also provide a unique opportunity to advance sustainability education and behavioural change at scale. As in most sectors, digital sustainability initiatives within universities remain narrowly focused on carbon calculations, typically providing static feedback that limits opportunities for sustained behavioural change. To address this gap, we propose Eco-Bee, integrating large language models, a translation of the Planetary Boundaries framework (as Eco-Score), and a conversational agent that connects individual choices to environmental limits. Tailored for students at the cusp of lifelong habits, Eco-Bee delivers actionable insights, peer benchmarking, and gamified challenges to sustain engagement and drive measurable progress toward boundary-aligned living. In a pilot tested across multiple campus networks (n=52), 96% of the student participants supported a campus-wide rollout and reported a clearer understanding of how daily behaviours collectively impact the planet's limits. By embedding planetary science, behavioural reinforcement, and AI-driven personalisation into a single platform, Eco-Bee establishes a scalable foundation for climate-conscious universities and future AI-mediated sustainability infrastructures.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
