All work
Geospatial intelligence for equitable BTS infrastructure planning
Machine learning and geospatial analysis used to prioritize cellular infrastructure deployment toward universal internet access.
- Role
- Research Team
- Period
- 2023 to 2024
- Location
- Indonesia
01Situation
Indonesia's universal internet access target required a systematic way to prioritize where new Base Transceiver Stations (BTS) should be deployed.
02Approach
Contributed to a machine learning framework integrating environmental suitability, infrastructure readiness, fiber optic proximity, and internet demand to prioritize BTS development.
03Finding
Combining spatial suitability with projected demand produced a practical decision framework for identifying high-priority infrastructure investment areas.
04Outcome
Published in Computers, Environment and Urban Systems, providing a transferable framework for equitable digital infrastructure planning.