Real-Time Operations Dashboards

Operations data, on the floor

Most plants already have the data: output, takt, quality, downtime, all flowing through MES and SCADA systems. What the floor sees is usually something else — a TV running a stale browser tab, a whiteboard updated at shift change, numbers nobody trusts. The gap between what operations knows and what the floor sees costs real time.

TelemetryOS closes that gap by running dashboards as applications on managed screens. A wallboard app built with the React SDK reads live from your MES, historian, or BI platform — TelemetryOS enables applications to connect to any REST API — and shows the floor its actual numbers as they change. Because screens, kiosks, and sensors are applications on one platform, a sensor event can flip a board to an alert state the instant a station goes down: red banner, downtime clock, affected line called out, then back to normal when it clears.

The floor is a hostile place for fragile setups, so resilience lives at the device. TelemetryOS devices cache and execute locally, keeping dashboards on screen through network drops and resyncing when connectivity returns. A board that must be trusted can't be one router reboot away from blank.

One fleet across lines, shifts, and plants

A dashboard program rarely stops at one screen. Line boards, andon-style alerts, shipping-dock status, break-room KPIs, and safety messaging all want screens — and without a platform, each becomes its own mini-project with its own PC under a desk. TelemetryOS runs all of them as one fleet from one console, with content targeted per line, shift, or site.

That console view is what makes the program operable. IT sees device health and proof-of-play across every plant; a dead screen on a night shift is an alert, not a surprise during the morning Gemba walk. And because dashboards are applications deployed git-to-screen, improving them is a code push: add a metric, refine an alert threshold, roll it to every plant at once. Edge AI extends the same screens further — on-device computer vision and LLMs run locally, private by design, with no production data making a cloud round-trip.