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Data Management

Engineering-grade fleet data management with structure, control, and access

AutoPi provides an end-to-end data layer for telematics and fleet operations. Raw CAN, CAN FD, OBD-II, GNSS, and event streams from AutoPi devices are ingested, decoded where relevant, and stored using consistent schemas, timestamps, and identifiers. This gives engineering and operations teams a deterministic foundation for analytics, monitoring, and automation instead of ad hoc log files or vendor-specific exports.

The platform separates ingestion, processing, and access. You define which signals to capture, at which sampling rates, and under which conditions they are transmitted. On-device filters and aggregation reduce noise and bandwidth consumption. In the backend, scheduled jobs handle retention, rollups, and exports so that high resolution data can be archived, downsampled, or forwarded into external systems without manual handling.

Fleet data integrates into existing BI, ERP, and maintenance systems through REST, MQTT, and webhooks, or can be consumed directly from AutoPi dashboards and APIs. Clear data ownership, versioned parsers, and traceability from individual signal samples to vehicles, trips, and configurations provide a controllable and auditable data backbone suitable for both day-to-day operations and long term engineering analysis.

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AutoPi CAN-FD CAN Bus loggers
Solution Highlight

Transform fleet data into a powerful tool

AutoPi provides a structured, engineering-focused data pipeline for fleets that generate high volume and high frequency signals. Devices capture raw CAN and OBD-II frames, GNSS samples, and event streams at the vehicle edge, enrich them with metadata such as VIN, vehicle type, and firmware version, then uplink the result into a backend that is designed for time series workloads and traceable event processing.

Data pipeline transforming vehicle signals into structured, actionable fleet data

The AutoPi fleet data management layer scales from small pilots to production fleets with thousands of vehicles that stream continuous CAN, OBD-II, GNSS, and sensor data. Sampling rates, trigger conditions, and compression strategies can be tuned per project so that cellular usage, storage footprint, and data resolution match concrete requirements. Preprocessing at the edge removes redundant samples and aggregates fast signals, which lowers transmission costs while preserving information content.

Real time and historical data follow the same schemas and indexing strategy, which simplifies correlation of events across vehicles and time. This enables dashboards, anomaly detection, alerting, and automated reporting without per-project restructuring of payloads. Trip segmentation, event rules, and time series alignment make it possible to relate low level frames to higher level KPIs such as utilization, fault frequency, and energy use per route.

Access control is enforced through role-based permissions and scoped views so that sensitive operational and vehicle data is only accessible to the intended users and systems. All communication uses device certificates and TLS encryption, and audit logs together with configurable retention policies allow the platform to be aligned with internal security, compliance, and data governance requirements.

With an open data pipeline, AutoPi integrates with data lakes, BI platforms, ERP and maintenance systems, and custom applications. Enriched datasets can be exported in batch, consumed through REST APIs, subscribed to via MQTT topics, or delivered to external endpoints through webhooks. The platform is intended to fit into existing architectures instead of replacing them and provides a consistent way to keep fleet data clean, synchronized, and interoperable across systems.

Related Features

Key features to boost your fleet data management

AutoPi turns raw telematics signals into a governed data layer. These capabilities control which users and systems can access specific data sets, how that data is exposed, and how it moves between vehicles, AutoPi Cloud, and external infrastructure.

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Secure and customize user permissions

Control access to fleet data with role-based permissions that can be scoped per customer, project, vehicle group, or feature set. Operational staff, engineering teams, and external partners can work in the same environment while seeing only the vehicles, signals, and tools that are relevant to them. All changes and sensitive actions can be written to audit logs with user, time, and context information.

AutoPi Cloud
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Shape how data is exposed

Configure custom endpoints, message topics, and payload layouts so that AutoPi data matches the contracts used by your BI, ERP, maintenance, or customer-facing systems. Map raw and derived signals into domain-specific models, control aggregation windows and units, and publish only the data each consumer requires in order to reduce coupling and simplify long term maintenance.

Custom endpoint
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Streamline your data flow

Use AutoPi as an IoT gateway for telematics workloads. Ingest CAN and OBD-II frames, GNSS data, and sensor inputs at the edge and forward them via REST, MQTT, and webhooks to cloud services, data lakes, or message buses. Local buffering, retry logic, and throttling make sure that intermittent networks and backend limits are handled in a predictable way while keeping fleet data flowing.

IoT gateway
Products

Better fleet data insights

Build a reliable, high resolution data pipeline for your fleet. AutoPi hardware captures the signals, and AutoPi Cloud structures, stores, and distributes them so that they are ready for analytics, dashboards, and operational automation.

AutoPi TMU CM4 telematics hardware

Streamline data collection

The AutoPi TMU CM4 is a Linux based telematics unit for engineering-grade data acquisition and edge processing. It logs raw CAN and CAN FD frames, OBD-II data, GNSS samples, and events with precise timestamps and device identifiers. Configurable filters, triggers, and compression profiles define which data is transmitted, stored locally, or used only for on-device logic. Dual CAN interfaces, 4G or LTE connectivity, and extensible I and O make the device suitable for both internal combustion and battery electric platforms.

AutoPi TMU CM4
AutoPi Cloud dashboard widget

Centralize your fleet data

AutoPi Cloud aggregates data from every connected vehicle into a structured, searchable, and exportable repository. Trip logs, live events, alerts, diagnostic records, and configuration changes are stored with consistent identifiers so that they can be queried directly or routed into other systems through REST, MQTT, and webhooks. Over the air updates, parser versioning, and role-based access control help keep the data model synchronized across devices and projects while maintaining clear boundaries between customers and environments.

AutoPi Cloud
Why AutoPi?

Inspiring industry innovators: our role in
your success

AutoPi gives engineering teams, data analysts, and fleet operators a transparent and programmable data foundation. Instead of a closed telematics stack, AutoPi exposes raw signals, structured datasets, event logs, and device metrics so that custom analytics, automation, and integrations can be implemented on top. From hardware configuration through to data export, the platform is designed to support repeatable processes, long term maintainability, and the level of observability that technical teams expect when they build or extend fleet solutions.

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Something unclear?

Frequently asked questions

Fleet data management is the end-to-end process of acquiring, structuring, storing, and exposing data that originates from vehicles and drivers. It covers ingestion from telematics units such as CAN and OBD-II, GNSS, and auxiliary sensors, normalization into consistent schemas, application of business logic such as trips, events, and KPIs, and distribution of the resulting datasets to dashboards, APIs, and downstream systems.

AutoPi can collect raw CAN and OBD-II messages, EV battery metrics where supported, GNSS position and speed, trip and ignition events, diagnostic trouble codes, and custom sensor inputs such as temperature, door switches, or digital and analog I and O. All streams are timestamped, tagged with device and vehicle identifiers, and made available for real time use and long term analysis.

Data is stored using consistent, versioned schemas that link signals and events to vehicles, devices, and trips. Time series, events, and configuration changes are all recorded with timestamps so that system state can be reconstructed for any interval and KPIs can be recalculated when models change. Retention policies and export options control how long raw and processed data is kept and which subsets are archived or moved into external storage.

Yes. AutoPi supports exporting datasets and streaming telemetry into external systems through REST APIs, MQTT topics, and webhooks. Many customers use AutoPi as the ingestion and normalization layer and then forward structured data into data lakes, warehouses, or stream processing platforms where it is combined with business data and used for reporting and modeling.

AutoPi devices can filter, aggregate, and compress data at the edge before transmission. Sampling rates and capture rules are configurable per use case so that only relevant packets are sent. On the backend, buffering, batching, and retention policies ensure that large fleets and high frequency CAN or GNSS streams remain manageable without overloading networks or storage subsystems.

Data is transported over TLS encrypted connections that use device bound credentials. Access to fleet data, APIs, and management functions is controlled with user roles and permissions. Data ownership, retention, and export rights are defined in your commercial agreement, and AutoPi can be configured to export or synchronize data regularly into your own infrastructure for long term storage and compliance.

Yes. AutoPi is used in mixed ICE and EV fleets. Where supported by the vehicle, EV specific signals such as state of charge, charging power, battery temperature, and range indicators can be collected and processed together with conventional metrics such as fuel use, mileage, and engine diagnostics so that a single data model covers the entire fleet.

AutoPi exposes fleet data through REST APIs, scheduled exports, and streaming interfaces that BI tools or integration layers can consume. You can query the AutoPi backend directly, push data into your own databases on a schedule, or subscribe to event streams that feed live dashboards, scheduled reports, and analytic models.

Developers can integrate with AutoPi through documented REST APIs, MQTT topics, and webhooks. On the device, standard Linux tooling can be used to deploy custom scripts, services, and integrations. Data teams can rely on stable schemas, event types, and export formats, which simplifies the creation of pipelines, models, and dashboards on top of AutoPi data.

A typical pilot starts with a small number of AutoPi devices installed in representative vehicles, AutoPi Cloud access or an API endpoint in your own backend, and a short list of concrete objectives such as improving visibility, validating KPIs, or integrating data into a specific system. Once the data model and integration path are validated, the same configuration can be rolled out across the wider fleet with only minor adjustments.

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