Reduce data at the source.
Integrate the compact C SDK where hardware and workload constraints allow local batching.
IoT data compression solution
Lossless IoT data compression for sensor and telemetry payloads.
ZNano reduces repeated structured data before transmission while preserving exact recovery of the original payload.
Designed for sensor fleets, smart meters, industrial equipment and remote assets, ZNano can operate on a device, at a gateway or inside a telemetry backend.
The bandwidth problem
IoT payloads are small. Fleets make them expensive.
A single sensor message may contain only a few bytes, but repeated transmission across thousands of devices turns small inefficiencies into airtime, bandwidth, storage and operating pressure.
ZNano targets the structured application payload itself. It looks for recurring patterns across aligned telemetry records, compresses them losslessly and reconstructs the original bytes on decode.
- Reduce repeated sensor and meter payloads.
- Preserve exact byte-for-byte reconstruction.
- Keep the existing network and application protocol.
- Deploy on devices, gateways or backend services.
IoT solution architecture
Compress before constrained transport or storage.
ZNano is a payload transformation layer. It does not replace LoRaWAN, NB-IoT, MQTT, device security or protocol validation.
Sensor readingsStructured recordsZNano compressionNetwork or storageZNano decodeOriginal telemetry
Aggregate and compress streams.
Group aligned device records before forwarding data through costly or intermittent links.
Decode, verify and replay.
Recover original payloads deterministically for downstream applications and audit workflows.
IoT applications
Built for repeated operational telemetry.
The strongest fit is structured data that repeats over time rather than already compressed media or random encrypted bytes.
Electricity, water and gas readings produced at predictable intervals.
Temperature, vibration, pressure, machine state and maintenance telemetry.
Location, motion, engine and cold-chain records from distributed fleets.
Soil, irrigation, livestock and environmental sensor data.
Maritime, mining, energy and field systems using expensive or intermittent links.
Traffic, parking, air quality, buildings and municipal sensor networks.
Evaluation
Measure with your real payload structure.
Compression performance depends on record alignment, field repetition, batch size and target hardware. ZNano therefore provides a live simulation and a custom payload workflow instead of promising one universal ratio.
The public verified evidence set reports structured reductions from 23.46% to 90.85%, with exact reconstruction checked using SHA-256. Review the methodology and test representative records before planning production capacity.
Good evaluation inputs
- Representative fixed-width records.
- Realistic batch sizes and reporting intervals.
- Target CPU, memory and energy constraints.
- Round-trip integrity verification.
Related technical paths
Go deeper into the deployment constraint.
Use the focused guides when your search starts with hardware limits or a specific LPWAN transport.
Embedded telemetry compression
Architecture choices for MCU-class and constrained edge environments.
Read the embedded guideLoRaWAN payload compression
Application-payload reduction before data enters the LoRaWAN stack.
Read the LoRaWAN guideZNano product and demo
Technical evidence, use cases, integration options and a live stream simulation.
Explore ZNanoIoT deployment
Evaluate ZNano on your sensor data.
Bring a representative telemetry sample and measure compression, decode and integrity before making an integration decision.