Digital Twin Synchronization Demo

Watch physical state, reported twin state, desired state, and command acknowledgement move through a synchronization loop.

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digital-twin

architecture

synchronization

interactive

Interactive digital twin synchronization demo with moving reported-state and command tokens, synchronization mode presets, latency and freshness calculations, state-drift chart, and mobile-friendly learning support.

Digital Twin Sync Loop Reported vs Desired

A digital twin is useful only when learners can see what is fresh, stale, and commanded.

Step through the loop from physical device to edge gateway, digital twin, and operator app. The demo keeps the moving tokens, live metrics, state values, and diagnosis synchronized so the freshness tradeoff is visible in a few minutes.

199 ms Estimated P95 twin age

0.5% Estimated state drift

0.74 Mbps Upstream telemetry load

107 ms Command acknowledgement

TrySet Sync interval to 1.2 s and One-way latency to 120 ms, then press Step through physical change, publish, cloud update, command, and acknowledgement. Increase Jitter for a second run.

ObserveReported-state age and P95 freshness grow with periodic wait, transport delay, and jitter. Desired state can lead the physical device until the command acknowledgement completes.

ExplainA physical change waits, on average, half a polling interval before transport; edge work, cloud write, command delivery, and queue delay add to that freshness budget.

Technical boundariesThe timing model excludes broker retry distributions, concurrent writes, clock error, actuator interlocks, field-level conflict resolution, and lost acknowledgements.

Colour keyemerging paradigms identitycurrent / primaryreference / datasuccesscautionerror / failure

What moves?

Reported state flows from the physical asset to the twin. Desired state flows back as a guarded command.

What changes?

Sync mode, interval, latency, event threshold, and volatility change how old the twin is when a decision uses it.

What should learners notice?

A connected twin is not automatically trustworthy. Freshness, drift, and acknowledgement must match the use case.

Animated synchronization loop

Reported state forward, desired state back

Stage 1 of 6

Physical asset

Sensors measure the process and stamp the observation with device time.

Edge gateway

The gateway filters noise, detects events, batches, and buffers telemetry.

Digital twin

The service updates reported state, desired state, version, and timestamp.

Operator app

Dashboards and automations use the twin only if its age is acceptable.

Physical state --

Reported twin state --

Desired state --

Sync decision --

State drift over time

Physical state and twin view do not move at the same time

The chart shows why a twin may look connected while still lagging the real asset. The desired line is what the app wants the physical asset to reach.

Plain-language diagnosis

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Controls

Run the demo

Use scenarios and modes to see the loop quickly, then tune the parameters that usually make a twin stale.

Synchronization mode

Sync interval --

Periodic wait is roughly half the interval for random changes.

One-way latency --

Jitter --

Process volatility --

Event threshold --

Desired-state change --

Scenario -- Payload -- Target --

How to read the loop

The reported token carries observed physical state to the twin. The desired token carries an operator or automation command back. A command should be held when the twin is too old or the reported value is far from the current physical estimate.

Metric formulas used in this demo

P95 age = wait + one-way latency + edge work + cloud write + 1.65 x jitter + queue delay.
upstream Mbps = events/s x payload KB x 8 / 1000 using decimal networking units.
state drift ~= volatility x age + threshold penalty.
acknowledgement time ~= 2 x one-way latency + jitter + command processing.

Mode selection guide

Mode	Best fit	Main risk
Continuous	Fast process monitoring and control-adjacent twins.	High bandwidth, storage, and power use.
Periodic	Dashboards, logs, and slow processes.	State changes wait for the next heartbeat.
Event-driven	Sparse changes with reliable edge detection.	Slow drift below the threshold can stay hidden.
Hybrid	Most operational twins that need heartbeats plus urgent events.	More tuning and observability work.

Technical guardrails

This is a teaching model, not a vendor benchmark. A production twin should measure device timestamps, clock skew, gateway queue time, broker retry behavior, twin-write latency, command acknowledgement, and stale-field policy. Average latency alone is not enough for command or safety decisions.