B · Hive
B · Hive
Service 03

Payload & edge computing integration

Onboard data processing, in real time.

We integrate companion computers (NVIDIA Jetson, Raspberry Pi) for computer vision, tracking, vision-aided navigation and low-latency streaming, with precise sensor synchronisation and georeferencing.

Strengths

  • ROS 2 architecture for the dialogue between avionics, companion computer and payload
  • NVIDIA Jetson integration with onboard AI inference
  • Time synchronisation and data georeferencing (GNSS RTK/PPK)
  • In-flight processing: object detection, assisted inspection, operator alerts

Intelligence onboard

Modern data collection asks the drone to extract operational value in flight:

  • Real-time computer vision — recognition of anomalies on infrastructure, thermal surveys, counting and tracking, with immediate alerts on the ground.
  • Vision-aided navigation — useful where the GNSS signal is weak or absent, in covered industrial environments or close to structures.
  • Ready-to-use data — precise alignment between the GNSS receiver and the optical/thermal sensors for datasets that are immediately usable in photogrammetry or GIS.

Typical deliverables

  • Engineered payload pod with dedicated wiring
  • Configured onboard software and a test scenario
  • Data-interface documentation

Technologies & toolchain

ROS 2 NVIDIA Jetson & AI accelerators MAVLink Camera Protocol Low-latency video streaming

Standards & compliance

  • EMI shielding and thermal management of high-power loads
  • Protected, quick-release mechanical enclosures
  • Documented data interfaces toward the client's systems

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