| Details | |||||
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| Supervisor | Chiam Yin Kia | Department | Software Engineering | ||
| Semester | Semester 2 | Session | 2024/2025 | ||
| Mode | CONVENTIONAL | No of Student | 2 of 2 students Full | ||
| Project Details | |||||
| Project Title | Dynamic Rule-Based GIS Modeling for Business Location Suitability Using GenAI | ||||
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| Description | Description This project aims to develop a
dynamic GIS model that uses rule-based logic and Generative AI (GenAI) to help
businesses select optimal locations based on user-defined criteria such as foot
traffic, competitor density, accessibility, and demographic analysis. The
system will allow users to input business preferences, and AI will generate
suitability maps dynamically. General Objectives 1. To automate business location selection using
AI-generated rule-based GIS models. 2. To extract key decision factors from user inputs using
GenAI. 3. To visualize business suitability dynamically based on
spatial criteria. 4. To integrate demographic and economic data for
enhanced decision-making. Modules Involved 1. Rule-Based GIS Suitability Module: Computes location
scores based on AI-generated criteria. 2. GenAI Input Analysis Module: Extracts key preferences
from user input. 3. Spatial Data Processing Module: Integrates Road networks, competitor locations, and economic data. 4. Interactive Web Visualization Module: Displays results dynamically |
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| Potential Collaborators | Kleos Technologies: Provides and supervises GIS modeling and AI research support. NOTE: The collaborators can provide training for the OpenAI, but no sponsorship for the subscription |
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| Tools | Programming: Python, JavaScript; GIS Software: ArcGIS, QGIS, Leaflet; AI Model: OpenAI GPT, LangChain; Data Sources: Government Economic Reports, OpenStreetMap | ||||
| Assigned Students |
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