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// vehicle-bus logging
AutoPi CAN-FD Pro
Start here for J1939, CAN FD and vehicle-bus data logging. Confirm the vehicle network, connector and signal definitions.
Explore CAN-FD ProCommercial Trucking
Real-time telemetry and control for trucking fleets
AutoPi collects CAN/J1939, OBD-II, GPS and environmental sensor data from tractors, trailers and reefers. Devices run at the edge, buffer when offline, and sync to the cloud over secure channels. You define loggers, thresholds and actions; the platform records events, creates alerts, and exposes data through APIs and exports.
Agree on the required signals, sampling rates, trip detection and geofences for depots and customer sites. Validate data availability and decoding by OEM, model and year. A vehicle connector alone does not guarantee access to every requested parameter.
The system supports multiple network protocols including CAN-FD, J1939, ISO 14229 (UDS) and ISO 15765. Data from these channels can be combined with GPS and accelerometer data to build a continuous timeline of vehicle performance, cargo conditions and driver activity. Each message is timestamped at the source, enabling sub-second event correlation across vehicles in the fleet.
Data is stored locally on the device when cellular connectivity is unavailable, ensuring zero data loss during coverage gaps. Once reconnected, buffered data is transmitted using a compressed and signed protocol. This guarantees delivery integrity even for large fleets operating across regions with limited coverage. Transport encryption and per-device authentication prevent tampering or injection of unauthorized data.
The platform can integrate directly with existing systems via REST, MQTT, or webhook-based APIs. Users can export telemetry to fleet management software, maintenance systems, or analytics pipelines. Real-time alerts, diagnostics and firmware updates can all be automated through rule-based jobs and OTA templates, minimizing manual intervention while maintaining full operational control.
Discuss a trucking PoC
Truck Performance Monitoring
Capture available engine and powertrain metrics from CAN/J1939. Configure sampling and thresholds for validated signals such as coolant temperature or battery voltage. Maintenance-system work orders require integration with your existing workflow.
Cargo Monitoring
Log temperature, humidity, door state and shock for each load. Set per-lane or customer thresholds and receive excursions in real time. Generate shipment PDFs or JSON exports with sensor traces, setpoints, and handling notes for audit and claims.
Driver Behavior Analysis
Derive events for harsh acceleration/braking, overspeed and idling. Map drivers via RFID/Bluetooth or assignment. Produce adherence metrics per driver, lane and vehicle class. Optionally feed coaching systems through webhooks.
Trip and Geofence Monitoring
Configure geofences for depots and customer sites, review trips and monitor entry, exit and dwell time. Use the resulting data in your TMS or BI integration. Route planning and optimization require a separate routing engine or integration.
Real-Time Monitoring
Real-time truck performance monitoring
Devices read vehicle networks (CAN, CAN-FD, J1939, ISO 15765) and GPS at configurable intervals. Edge filters reduce bandwidth by aggregating and compressing non-critical signals while retaining full-rate data for thresholds and faults. When connectivity drops, data buffers locally and syncs on reconnection.
Fleet configuration is template-driven: loggers, triggers, jobs and returners are versioned and applied per OEM/model year. OTA updates support staged rollout and rollback. Every change is stored with author, timestamp and diff for audit.
Typical triggers include repeated DTCs over a window, temperature gradients exceeding a slope, voltage sag during crank, and coolant/oil threshold crossings. Each trigger can execute a job (diagnostic capture, service command) and emit notifications to email, webhook or MQTT with deduplication and retry policies.
Driver Monitoring
Cargo and driver monitoring with audit trails
Pair tractors and trailers automatically and log custody events. For cargo, define limits per load and record excursions with sensor traces and GPS. For drivers, aggregate behavior events and correlate with fuel and maintenance outcomes. Reports can be scheduled to PDF/CSV or delivered as JSON to downstream systems.
Access is controlled by roles and nested accounts. Data access follows tenant boundaries. All actions (command execution, config changes, firmware pushes) are logged with device ID, user, and result code.
Integration options include REST pull, MQTT topics with QoS and retained messages, and webhook callbacks with signed requests. For bulk analytics, scheduled exports provide partitioned files by day, vehicle group or customer, suitable for data lake ingestion.
Something unclear?
Frequently asked questions
Fleet operations using heavy vehicles for goods transport. The platform treats each asset (tractor, trailer, reefer) as an independent data source with its own signals and lifecycle. Data is normalized, time-aligned, and stored for analytics, compliance, and automation. Assets can be grouped by customer, location, lane, or contract so policies, alerts, and exports match the operational structure.
Rule-based actions on live data: open a ticket on repeated DTCs, alert on temperature drift, flag idling above a threshold, or export a trip summary after
trip_end. Rules can be staged on a subset of vehicles and rolled out fleet-wide after validation. Actions include diagnostic capture, webhook to TMS, or placing the vehicle into a maintenance state with notifications to a defined channel.
Cargo monitoring can reveal temperature excursions and handling events when compatible sensors or reefer data are available. Confirm sensor hardware, power, installation and connectivity. Load-level reporting, compressor data and chain-of-custody workflows depend on available signals and an agreed integration scope.
Events are computed from speed, acceleration, IMU, and context (road type, geofence). Drivers are linked via RFID/BLE or assignment. Results feed safety reviews, coaching workflows, and-if enabled-policy enforcement on idling and speed. Reports aggregate by driver, vehicle, customer, or lane to compare adherence and outcomes objectively.
Data can be consumed via REST, MQTT, and scheduled exports (CSV/JSON/PDF). Webhooks are available for trips, geofence events, DTC alerts, and cargo excursions. Authentication and rate limits are per tenant; all calls are logged with request IDs. For bidirectional control, commands execute on devices with result logs and exit codes. ELD/HoS data can be correlated with trips for compliance analysis if provided.
Geofences for depots and customer sites generate enter/exit events and dwell times. Combined with trip KPIs (ETA error, route deviation, idle ratio), this highlights congestion and unauthorized stops. Exports feed routing engines or TMS to adjust lanes and schedules. Daily summaries per lane reduce fuel waste and improve on-time arrival.
Devices read vehicle networks at configurable intervals, with acceptance filters and burst capture on triggers (repeated DTCs, threshold slopes, geofence entry). Templates are applied per OEM/model year so mixed fleets share a single control plane without losing signal depth. Decoding uses DBC/definitions; units and scaling are enforced for consistent downstream consumption.
Per-device authentication, transport encryption, and signed payloads. Role-based access with tenant boundaries. All actions (config changes, OTA, commands) are logged with user, device ID, and result code. Offline buffering preserves continuity; verified sync on reconnection prevents tampering or loss.
Reports (e.g., geofence summary, idling, lane KPIs) can run daily, weekly, or monthly. Results are delivered as PDF/CSV or to a webhook, and archived for retrieval. Exports can be partitioned by day, customer, or vehicle group for ingestion into TMS/BI/data lakes. Each export has a task ID, timestamps, and retention controls.
Purchase PoC devices for representative trucks after confirming hardware and installation requirements. AutoPi then helps extract the required data, including reverse engineering where needed. Agree the signals, integration work and acceptance criteria; validate the results before deciding on wider rollout.
// built around your industry
Choose a starting point for Commercial Trucking
Let's match your vehicles and data requirements to the right hardware, then explore your integration together. AutoPi Cloud is included with every AutoPi device.
Match hardware to the data
// fleet data
AutoPi Mini
For supported EV and OBD fleet data. Check make, model, year and required parameters before ordering.
Check Mini compatibility// custom edge software
AutoPi TMU CM4
For Docker workloads and custom edge software. Confirm interfaces and any additional hardware needed.
Explore TMU CM4// delivery scope
Define what your project needs
- Included
- AutoPi Cloud, plus the selected device's documented hardware and standard software capabilities. Check the supplied accessories and connectivity plan for your chosen configuration.
- Configure
- Supported signals, sampling, trips, geofences and data delivery for the chosen device. Validate connectors, power, storage and retention limits.
- Custom development
- Missing signal decoding, external sensor integration and business-system workflows require assessment and an agreed scope.
// your proof of concept
Validate on your vehicles
We'll help you choose devices to purchase for representative vehicles, then work with you to extract the required data, including reverse engineering where needed. Together, we'll agree the signals, installation, integration work and acceptance criteria before expanding the deployment. Feasibility and scope depend on your vehicles.
Discuss your PoC
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Still have questions?
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