让不懂代码的人也能用对话分析空气质量数据
VayuChat: An LLM-Powered Conversational Interface for Air Quality Data Analytics
- 用大模型把自然语言转为可执行代码和可视化结果
- 整合了1000+监测站、人口与治污资金数据
- 适合政策制定者、研究者和普通公众使用
空气污染每年导致印度约160万例过早死亡，但决策者难以将分散的数据转化为行动。现有工具需专业知识且仅提供静态仪表盘，关键政策问题仍无法解决。我们提出VayuChat，一个对话式系统，可通过自然语言问答实现空气质量、气象与政策项目分析，并生成可执行的Python代码和交互式可视化。该系统整合中央污染控制委员会（CPCB）超过1000个监测站数据、省级人口信息及国家清洁空气计划（NCAP）资金记录，构建统一接口。通过大语言模型驱动，用户可仅凭对话完成复杂环境数据分析。平台已公开部署于https://huggingface.co/spaces/SustainabilityLabIITGN/VayuChat，更多信息请观看视频：https://www.youtube.com/watch?v=d6rklL05cs4。
原文摘要 · Abstract (English)
Air pollution causes about 1.6 million premature deaths each year in India, yet decision makers struggle to turn dispersed data into decisions. Existing tools require expertise and provide static dashboards, leaving key policy questions unresolved. We present VayuChat, a conversational system that answers natural language questions on air quality, meteorology, and policy programs, and responds with both executable Python code and interactive visualizations. VayuChat integrates data from Central Pollution Control Board (CPCB) monitoring stations, state-level demographics, and National Clean Air Programme (NCAP) funding records into a unified interface powered by large language models. Our live demonstration will show how users can perform complex environmental analytics through simple conversations, making data science accessible to policymakers, researchers, and citizens. The platform is publicly deployed at https://huggingface.co/spaces/SustainabilityLabIITGN/ VayuChat. For further information check out video uploaded on https://www.youtube.com/watch?v=d6rklL05cs4.
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