nesteye

One edge system. A growing model library.

Cameras, sensors, local AI, and barn-level intervention work together today, while the same installed frame creates a path to new monitoring models.

One barn with the nesteye system installedCross-section of a poultry barn. Three ceiling cameras look down over the floor, a sensor on the wall records temperature, humidity and air, an edge computer on the opposite wall runs the models, and light and sound fixtures hang from the ceiling. A dashed line leaves the barn to an operator dashboard showing alerts and trends. A small pile of birds near one wall is outlined as the signal.overhead cameraslight and soundsensortemperature, humidity, airedge computermodels run here, in the barna pile formingoperator dashboardalerts and trends, not raw video

Built around the barn, not the cloud.

Decisions stay inside the barn. Only status, trends, and alerts need to leave it.

  • Overhead cameras on power-over-Ethernet keep the whole flock in view, day and night.
  • Environmental sensors log temperature, humidity, and air quality on the same timeline as the birds.
  • A small edge computer in the barn runs every model locally, in under half a second, so nothing time-sensitive waits on the cloud.
  • Addressable lights and speakers break up a confirmed pile without waiting for a barn walk.

Five signals. One place to look.

Piling, weight, environment, disease monitoring, and the dashboard operators actually use.

Piling

Detect and disperse dangerous piling.

Overhead vision identifies developing clusters while adaptive light and sound can intervene inside the barn.

Repeated-frame confirmation helps separate a real event from ordinary flock movement before the system responds.

Live camera frame from a commercial poultry house with every bird outlined by the segmentation model
Live segmentation

Every bird outlined, every frame.

A cluster has to persist across frames before the system intervenes.

What the system does today.

Fecal-pattern monitoring for Salmonella risk runs on the same cameras. See the research. Commercial onboarding is pilot-led and barn-specific.

  • Piling

    Repeated-frame confirmation helps separate a real event from ordinary flock movement before the system responds.

  • Weight

    A broader overhead view reduces reliance on stressful catches and small, biased walk-over samples.

  • Environment

    Environmental signals stay connected to flock activity instead of living in a separate operating view.

  • Dashboard

    Only lightweight operational data leaves the barn; time-sensitive inference stays on the edge.

  • Disease monitoring

    Disease signals appear in the dashboard with barn context so teams can investigate and respond sooner.

Start with one measurable pilot.

Every installation begins with barn fit, operating goals, and a shared definition of success.

  • Survey

    Review the barn layout, camera coverage, network access, power, and operating goals.

  • Install

    Mount cameras and sensors, connect the edge computer, and calibrate the system for the house.

  • Pilot

    Measure performance against an agreed operating baseline before broader deployment.

The practical details.

Discuss a pilot

A typical nesteye system combines overhead PoE IR cameras, an environmental sensor array, an Edge SoC box, and addressable light and audio hardware for intervention.

Start with one measurable barn.

Request a pilot