Nokia required a highly scalable data processing pipeline to transform raw urban mapping data into navigation-ready intelligence. The goal was to process massive volumes of LIDAR scans and panoramic street imagery collected from scanner vehicles and convert them into precise, usable map data. CyberHULL partnered with Nokia to design and implement a high-performance, parallelized processing architecture capable of handling noisy, inconsistent data at city scale—supporting multiple scanning vehicles operating daily across urban environments.
The key obstacles we needed to overcome to transform the digital experience.
Single drives produced terabytes of raw data from LIDAR point clouds, panoramic street-level imagery, and geospatial signals with inherent noise and drift.
Raw scans required heavy normalization and correction to filter noise and achieve precision.
Outputs needed alignment with known landmarks to ensure navigation-grade accuracy.
Pipeline had to support multiple vehicles operating continuously across urban environments.
Near-real-time readiness for navigation systems was essential—traditional sequential processing could not meet these constraints.
