RailEstate: An Interactive System for Metro Linked Property Trends
Access to metro systems plays a critical role in shaping urban housing markets by enhancing neighborhood accessibility and driving property demand. We present RailEstate, a novel web based system that integrates spatial analytics, natural language interfaces, and interactive forecasting to analyze how proximity to metro stations influences residential property prices in the Washington metropolitan area. Unlike static mapping tools or generic listing platforms, RailEstate combines 25 years of historical housing data with transit infrastructure to support low latency geospatial queries, time series visualizations, and predictive modeling. Users can interactively explore ZIP code level price patterns, investigate long term trends, and forecast future housing values around any metro station. A key innovation is our natural language chatbot, which translates plain-English questions e.g., What is the highest price in Falls Church in the year 2000? into executable SQL over a spatial database. This unified and interactive platform empowers urban planners, investors, and residents to derive actionable insights from metro linked housing data without requiring technical expertise.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
PolyFusionAgent: A Multimodal Foundation Model and Autonomous AI Assistant for Polymer Property Prediction and Inverse Design
Polymer discovery is central to fields ranging from energy storage to biomedicine, but it is hindered by an astronomically large chemical design space and fragmented representations of structure, properties, and prior kn…
Representation LearningDecoding street network morphologies and their correlation to travel mode choice
Urban morphology has long been recognized as a factor shaping human mobility, yet comparative and formal classifications of urban form across metropolitan areas remain limited. Building on theoretical principles of urban…
VILT: Video Instructions Linking for Complex Tasks
This work addresses challenges in developing conversational assistants that support rich multimodal video interactions to accomplish real-world tasks interactively. We introduce the task of automatically linking instruct…
RetrievalAI-assisted Human-in-the-Loop Web Platform for Structural Characterization in Hard drive design
Scanning transmission electron microscopy (STEM) has become a cornerstone instrument for semiconductor materials metrology, enabling nanoscale analysis of complex multilayer structures that define device performance. Dev…
A Generative AI System for Biomedical Data Discovery with Grammar-Based Visualizations
We explore the potential for combining generative AI with grammar-based visualizations for biomedical data discovery. In our prototype, we use a multi-agent system to generate visualization specifications and apply filte…