Telemetry: Complete Definition and Guide

What is telemetry?

Telemetry is the automatic, remote and continuous collection of measurements produced by equipment spread across the field: machines, vehicles, sensors, routers, satellite terminals, self-service kiosks. Each device measures what concerns it (temperatures, position, throughput, signal, counter, state of a component), sends it to a central platform, and that platform stores the history, visualises it and watches over the whole.

The word comes from measuring at a distance and first served rockets and racing cars. Today it names the data layer of any fleet of connected devices: without telemetry, a fleet of fifty routers or two hundred machines stays a list of addresses; with it, it becomes a system you can steer.

Telemetry differs from classic network monitoring in its scope: it goes beyond "does the device answer?" and reports business quantities (consumption, cycles, fill level, signal quality) used to invoice, plan maintenance or improve a service.

Why it matters

• Knowing before the customer: a drifting machine, a degrading link, a unit that stops answering are detected before the support call.
• Planned maintenance: counters and trends say when to intervene, instead of waiting for the failure or visiting every site on a fixed date.
• Usage-based invoicing: pages printed, kilometres driven, data consumed, hours of operation: reliable measurement is the basis of the invoice.
• Fewer trips: a remote diagnosis avoids one visit; a remote update avoids a hundred.
• Decisions on facts: which sites, which machines, which hours cause problems; where to invest, where to remove useless equipment.
• Customer portal: the same data, filtered, gives each customer a view of their own devices, consumption and incidents.

How it works

A telemetry chain has four stages. Measurement, on the device: a sensor, an internal counter, a metric read on a vehicle bus or through a router's interface. Embedded software (on the unit or a gateway) reads these values at regular intervals, timestamps them and prepares them.

Then transport: measurements travel to the platform over whatever channel is available, wired network, Wi-Fi, 4G/5G, satellite or a low-power network (LoRaWAN). The MQTT protocol is the most common for its lightness; some equipment is queried through its manufacturer's API (routers, satellite terminals) rather than sending by itself. When the network is unstable, the device keeps its measurements locally and sends them when the connection returns: that is the role of edge computing, which also filters data on site so that only the useful part travels.

Storage: measurements are time series (a value, a date, a device) and belong in a database built for that (TimescaleDB, InfluxDB), able to absorb millions of points and aggregate them by hour, day or site.

Finally, operations: dashboards from the fleet down to the device, a map of the sites, alert rules (threshold, missing signal, detected drift), notifications by email, SMS or ticket, and exports to invoicing or the customer portal. On large fleets, machine learning models detect the anomalies that fixed thresholds would miss.

Concrete example

KERN-IT practises telemetry on several kinds of fleets. The largest came out of Kenobi, a 24-month research project carried out with the operator Venn Telecom and co-funded by Innoviris and VLAIO: a vendor-independent network management platform that supervised more than 2,000 network points across Europe in real conditions. Each point reported its metrics (signal quality, packet loss, 3G/4G/5G links) through the nodes and the operators' APIs; the algorithms developed picked the best available antenna for each connected object, and a machine learning model detected problems ahead of classic alerts. The project's geographic data gave birth to GISWAN, the tool for visualising network quality in the field.

At the other end of the scale, the self-service print kiosks operated for a university copy service report their status and page counters to a central platform tied to the till, and connected sports machines send their usage cycles for maintenance. KERN-IT brings this experience together in PulseCore, its IoT and telemetry platform, available on a monthly lease or as a white-label product.

Implementation

1. Start from the decisions, not the sensors: which questions must the fleet settle (what to invoice, when to intervene, what to replace)? The measurements to collect follow from them.
2. Inventory the devices and their interfaces: what each piece of equipment already exposes (manufacturer API, bus, counters), what must be added (sensor, unit).
3. Choose the transport for the terrain: existing network, cellular, satellite, LoRaWAN; plan local retention during outages.
4. Store as time series with a retention policy: minute-level detail for a few months, aggregates for years.
5. Define the alerts with the operators: few rules, well chosen, sent to the right person; an alert that rings every day ends up ignored.
6. Connect to invoicing and the customer portal: telemetry that never leaves the technical dashboard earns nothing.
7. Roll out in steps: a pilot site, then the fleet, while watching the telemetry of the telemetry itself (silent devices, synchronisation delays).

Associated technologies and tools

• MQTT and Mosquitto: lightweight messaging protocol and broker for reporting measurements from devices.
• Manufacturer and operator APIs: Peplink, Starlink, SIM operators, vehicle CAN/FMS buses, queried from the platform.
• LoRaWAN and NB-IoT: low-power, long-range networks for sensors without power or network.
• TimescaleDB and InfluxDB: time-series databases for the measurement history.
• Grafana: dashboards and alerts on time series.
• Python (FastAPI, Django): collection, business rules, customer portal and exports, the foundation of the PulseCore platform.
• Mapping (KernMap, GISWAN): sites, vehicles and signal quality on a map.

Conclusion

Telemetry turns a fleet of devices into a system you understand and steer: each piece of equipment says what it is doing, the platform keeps the history, alerts the right person and feeds the invoice. Collecting data is the easy part; collecting the right data, keeping it available when the network falters and turning it into decisions takes experience. KERN-IT builds these chains from Kenobi's network nodes to self-service kiosks, and brings them together in PulseCore for companies that operate a fleet of connected devices.