24018 Development of a Climate Risk Aware Digital Business Twin Using Spatial Indexing and GeoAI

Project Title: 24018 Development of a Climate Risk Aware Digital Business Twin Using Spatial Indexing and GeoAI

Mentor: Nakul Gupta, Management Development Institute Gurgaon, India

Project Description:

This project aims to integrate cutting-edge GeoAI analytics and spatial indexing technologies to create a sophisticated Digital Business Twin model that overlays intricate business operations with dynamic climate risk data. The focus will be on mapping business data such as operations, supply chains, and market penetration against climate projections and historical weather patterns using advanced spatial data science techniques. The ultimate goal is to provide actionable insights that help businesses mitigate the risks posed by climate change and optimize their operations accordingly. This model will serve as a crucial tool for understanding and adapting to the spatial dimensions of climate impacts on business, leveraging state-of-the-art open-source tools such as KNIME and allied workflow technologies.

Tasks and Responsibilities:

This project involves collecting and managing diverse business and climate-related data, enhancing data retrieval and analysis efficiency through spatial indexing, and identifying patterns using GeoAI. The fellow will develop predictive models to assess the impacts of climate scenarios, integrate data using advanced data science techniques to build a Digital Business Twin, and create dynamic visualizations to depict business and climate risks. Responsibilities also include preparing detailed reports, leading collaborative efforts with a multidisciplinary team, ensuring project milestones are met, and disseminating research findings through publications and presentations. Preference will be given to candidates with experience in low code workflow tools such as KNIME, which will aid in streamlining these processes.

Minimum Qualifications:

The ideal candidate will possess a Master’s degree in Geographic Information Systems, Spatial Data Science, Business Analytics, Environmental Science, Computer Science, or a closely related field. They should have strong proficiency in spatial analysis tools and techniques, with practical experience using GIS software and Python. Demonstrated experience in machine learning, AI, or statistical modeling, especially within a spatial context is appreciated. The candidate should be open to be familiar with climate data and its applications in business or environmental research. We are looking for someone with good analytical, problem-solving, and communication skills who can effectively collaborate within an interdisciplinary team.

Terms of the Project: 6 Months