Project AIS(w)ARYAM

AI for Sustainable Infrastructure and Resource Planning, Analysis and Monitoring.



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  • Ease of Use

    Need for easy-to-use AI tools that can integrate with existing data collection efforts across urban governance sectors
  • Native Language support

    Interfaces that allow natural user interaction with native language support are essential for uptake across geographies
  • Ecosystem

    focus on urban ecosystem-level carbon audit and policy recommendations
  • Carbon Audit

    Data-driven awareness of anomalous regions allows govt agencies to focus, investigate and allocate resources
  • Sustainable Development

    Sustainable development relies on active citizen participation in micro-level policy making within the city ecosystem
  • About

    Discover our story in providing AI for Sustainable Infrastructure.

    Our Story

    Our core objective is to develop an AI tech stack framework for urban infrastructure monitoring, planning and analysis
    Hotspot (or anomaly) detection a well-known use case of AI-ML methods, with many existing methods allowing us to focus on translational research.

    Our Mission

    Our objective is designed for scalability, accommodating heterogeneous data from different municipal bodies. We aim to license the framework, data, insights, and policy recommendations to commercial entities for post-project sustainability. A decision theatre, offering AR-VR visualizations of urban infrastructure with geospatial maps, is also envisaged and can be commercialized for further support.

    Our Vision

    Our project envisions an AI CoE providing an integral AI fabric to support urban sustainability, rather than a vertical focused effort. A robust framework is planned, based on a feedback loop between the domain, users, and technology.

    Problem Statement

    Lack of user-friendly AI tools for infrastructure/resource monitoring and analysis, accessible to diverse stakeholders Efficient and fast identification of hotspots across sectors of urban governance (e.g. carbon footprint, mobility, buildings, flooding, pollution/waste management)

    Project Team

    IIT Hyderabad Core of ~20 faculty across CSE, AI, EE, MAE, CE, ChE, Des, E&M depts Overall involvement from 40+ faculty

    Contact Us

    Reach out to us for any inquiries or feedback.

    IITH Road, Near NH-65, Sangareddy, Kandi, Telangana 502285