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IoT

GPS Up-time Analysis and Reporting Tool

Role Sole Engineer (Software, Data Analytics)
Tools Python 3.X
Disciplines
Software

Problem & Context

GPS-equipped asset trackers periodically experience “blackouts”, where position data stops updating or becomes unreliable. The events can stem from GPS or cellular loss of signal (LoS). We needed a way to retroactively parse thousands of GPS logs/reports to find these events to prevent them in the future, and make performance improvements of our GPS device.

Scope of Work

Technical Approach

Parsed each log line to extract timestamps, incremental hex counters, GPS coordinates, charge state, and cellular metadata (towers, carriers).

Used the sequential nature of the logs to infer device state:

Repeated GPS timestamps across consecutive reports indicate GPS blackout.

Gaps in the incremental hex counter indicate loss of cellular connectivity.

Applied the Haversine formula to convert latitude/longitude pairs into distances travelled during blackout periods.

Produced a summarized report and machine‑readable output (e.g., CSV) for further analysis and visualization.

This is a snippet of the code…….

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Technical diagram or schematic would be displayed here

Results

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Project results visualization

Generated per‑device reports listing every blackout and server‑delay event, followed by a concise summary of device performance metrics that can be quickly reviewed by engineers or test teams.

Adapted the tool for GPS certification and regional testing, using the output to visualize blackout‑prone areas and tune device configuration for specific regions to minimize blackouts.