Mobile Signal Coverage Optimization in Atlanta
Abstract (300 words maximum)
This project applies graph theory and data analysis to mobile signal coverage optimization in Atlanta. From web-scraped AntennaSearch data, we construct a graph model of the signal towers and their coverage areas. We utilize graph colouring algorithms to assign frequencies and visualize coverage distribution optimally. The project integrates population density data to identify low-coverage regions and generates a Signal Strength Heatmap using inverse distance weighting. We use K-means clustering suggests ideal locations for new towers in poor-signal, densely populated areas. Implemented in Python, the solution combines graph theory, geospatial analysis, and machine learning to provide a comprehensive solution to mobile network infrastructure optimization. The outcomes offer valuable intelligence for telecommunications planning with the potential to improve service quality and streamline resources.
Academic department under which the project should be listed
CCSE - Data Science and Analytics
Primary Investigator (PI) Name
Joseph DeMaio
Mobile Signal Coverage Optimization in Atlanta
This project applies graph theory and data analysis to mobile signal coverage optimization in Atlanta. From web-scraped AntennaSearch data, we construct a graph model of the signal towers and their coverage areas. We utilize graph colouring algorithms to assign frequencies and visualize coverage distribution optimally. The project integrates population density data to identify low-coverage regions and generates a Signal Strength Heatmap using inverse distance weighting. We use K-means clustering suggests ideal locations for new towers in poor-signal, densely populated areas. Implemented in Python, the solution combines graph theory, geospatial analysis, and machine learning to provide a comprehensive solution to mobile network infrastructure optimization. The outcomes offer valuable intelligence for telecommunications planning with the potential to improve service quality and streamline resources.