Automated Location Data Extraction from Google Maps Using Python

Abstract

The rapid growth of location-based services has made geographic data extraction a crucial requirement for applications such as urban planning, business intelligence, logistics, and navigation systems. Google Maps provides extensive and accurate location information, but manual data collection is time-consuming and inefficient. This project presents an Automated Location Data Extraction System from Google Maps using Python, designed to systematically retrieve structured location data such as place names, addresses, geographic coordinates, ratings, and categories. The system leverages Python-based automation techniques, including web scraping, API integration, and data parsing, to collect and organize information efficiently. Extracted data is stored in structured formats such as CSV or databases for further analysis and visualization. The proposed approach improves accuracy, reduces human effort, and enables large-scale data collection while ensuring scalability and adaptability. This system can be effectively utilized in domains such as market analysis, route optimization, smart city development, and location-based decision support systems.