The commercial drone market is on pace to breach $58 billion by 2027, fuelling massive demand for purpose-built software across flight control, perception, and data analytics.
A modern UAV software stack spans mission planning, real-time telemetry, computer-vision inference, and post-flight data pipelines, each presenting its own set of engineering challenges.
Computer vision and on-board ML allow drones to execute complex tasks without human intervention: crop-health mapping, power-line inspection, stockpile volumetrics, and search-and-rescue pattern flights.
Reliability requirements are stringent: GPS-denied navigation fallbacks, battery-aware mission planning, real-time obstacle avoidance, and deterministic fail-safes are non-negotiable for commercial certification.
Airspace regulations differ widely by jurisdiction, but common mandates include geo-fencing, Remote ID broadcast, altitude capping, and comprehensive flight-log retention.
Kevin Oduya
Infrastructure Lead
Hands-on cloud and DevOps practitioner specializing in resilient architectures on AWS and Kubernetes.
