Project AIS(w)ARYAM

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

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Explore our institute's wide range of Projects..

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Center of Excellence in Sustainable Urban Development

Center advancing sustainable urban development through multidisciplinary research in water, infrastructure, sanitation, and future city technologies, including sociology of digital societies and innovative communication tools.

Objectives

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