/LOSAnalysis

This repository addresses a critical challenge in telecom: the inefficiency and resource intensity of traditional on-site line of sight (LOS) surveys for network expansion and upgrades. By leveraging advanced technologies, the solution streamlines the LOS survey process, minimizing the need for extensive on-site visits.

Primary LanguageJupyter Notebook

LOSAnalysis

Problem Statement:

Telecom companies struggle with time-consuming and resource-heavy on-site line of sight (LOS) surveys for network expansion and upgrades. This leads to delays, inefficiencies, and potential connectivity issues due to inaccurate planning.

methodology plan

Data Integration:

Utilize open-source weather APIs, satellite imagery and datasets for real-time data for model training and testing.

Data Processing:

Issue 1: Develop Python scripts for integration and preprocessing. Utilizing a U-Net CNN architecture for precise and efficient building detection in remote sensing imagery.

Issue 2: develop python scripts using Earth observation data from sources like NASA’s EOSDIS and ArcGIS for weather/climatic updates.

Issue 3: To determine terrain updates using the Eurosat Sentinel 2 data and implementing ResNet-50 for accurate terrain detection in aerial imagery.

LOS Analysis Mapping and Visualization:

Use Python libraries like Matplotlib or Ploting for dynamic visualizations, including heatmaps and 3D models.