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Collect the data needed to improve a specific fleet decision—not every signal a vehicle can expose. A useful starting dataset links each vehicle’s identity and operating context to its trips, utilization, energy use, condition, maintenance history, safety events, and business outcomes. Add a field only when it is reliable enough to use, can be joined to the right vehicle and time, and could change an operational action.
Start with the decision, then choose the data
AI is not a reason by itself to collect more data. Decide first what the fleet wants to improve: avoid breakdowns, use assets more effectively, control energy costs, coach safer driving, or meet a service commitment. Then work backward from the decision to the minimum inputs and recorded outcomes needed to evaluate it.
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For example, a maintenance model needs more than fault codes: it needs vehicle use, repair records, and the outcome of each repair. An energy analysis needs fuel or electricity alongside distance and operating context. A safety-coaching program needs event definitions and comparable exposure, not just a count of alerts.
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Build a core dataset around six data families
These are useful starting categories, not a requirement to capture every listed field. Begin with the families relevant to the decision at hand and verify that the data is available consistently across the vehicles in scope.
| Data family | Useful fields | What it can help answer | Source grounding |
|---|---|---|---|
| Asset context | Stable vehicle identifier, vehicle class and configuration, powertrain, and relevant equipment attributes | Are vehicles being compared within a meaningful class, configuration, and operating role? | GSA Fleet’s telematics materials and the U.S. Department of Energy’s Federal Energy Management Program guide describe fleet and vehicle data categories. |
| Movement and utilization | Miles or odometer readings, engine hours, days used, trip counts, idle time, and—when justified—GPS, trip history, geofence events, route, or mission context | Where are vehicles operating, how much are they used, and where do trips or jobs encounter delays? | GSA Fleet and the DOE/FEMP guide list location, trip, utilization, and idling measures. |
| Fuel and energy | Fuel consumed for combustion vehicles; electricity consumed or added for EVs; distance and idle time for comparison | Which vehicles or operating conditions are associated with changes in energy use or cost? | GSA Fleet and the DOE/FEMP guide identify fuel or energy consumption as relevant telematics data. |
| Vehicle condition | Diagnostic trouble or fault codes, battery status or voltage, oil life, coolant temperature, tire pressure, and maintenance alerts where exposed | Which vehicle may need inspection or service before it interrupts operations? | GSA Fleet and the DOE/FEMP guide describe engine, fault, component-status, and maintenance information. |
| Driver and safety context | Driver-to-vehicle association where needed, speeding or harsh-event signals, seatbelt events, collision notifications, and coaching or incident outcomes | Which event merits review or coaching, and what happened after intervention? | GSA Fleet and the DOE/FEMP guide describe coaching and safety-related telematics capabilities. |
| Business outcomes and provenance | Work or mission context, service result, work orders, parts, repair cost, downtime, timestamps, source or device, units, and data-quality flags | Did a prediction or operational change produce a meaningful result, and can the input be trusted? | Federal fleet reporting and 41 CFR § 102-34.340 address inventory, cost, and use data across lifecycle stages. |
For AI analysis, an observation should be joinable to the correct vehicle and time, with enough operating context to interpret it and an outcome against which to assess it. A location point without a mission or trip context may not explain a delay; a fault code without a repair outcome cannot establish whether a prediction was useful.
Match the minimum data to the fleet decision
Maintenance planning
Join fault events and component status to miles or engine hours, work orders, repair dates, parts, downtime, and recurrence. This makes it possible to check whether an alert preceded a repair or interruption and whether the issue returned. A fault code is an indicator, not a diagnosis: validate model outputs against technician findings and repair outcomes.
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Utilization and fleet sizing
Combine miles, days used, trips, and engine hours with each asset’s role, mission, and availability. Low trip counts can indicate spare capacity, but they can also reflect seasonal standby or specialized assignments. A utilization measure without role and availability context can lead to a poor reassignment or disposal decision.
Energy and idling
Relate fuel or electricity use to distance, duty cycle, route, load or mission, and idle time. Add weather or other context only when it is available and relevant to the operating question. The federal sources identify fuel or energy and idling as useful categories; they do not prescribe a universal causal model for explaining consumption.
Safety coaching
For each event measure, record its definition, vehicle type, relevant road or operating context, and exposure such as distance or time driven. Compare event rates over comparable exposure and review suspected false positives with drivers and safety staff. Record coaching and incident-review outcomes if the fleet needs to assess whether an intervention changed results.
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Dispatch and service reliability
Link trips and location events to routes or jobs, service windows, completed work, and exception records. Location history is useful when it supports a defined operational purpose; collection and access should reflect that purpose.
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Keep compliance records separate from operational telematics
An electronic logging device (ELD) is a defined hours-of-service record stream, not a complete maintenance, safety, or utilization dataset. FMCSA says ELD records include engine power and vehicle-motion status, miles, engine hours, driver and authorized-user identification, vehicle and carrier identification, and duty status. Drivers certify records and may annotate events.
FMCSA’s ELD Functions FAQs, revised March 10, 2022, describe location recording at 60-minute intervals while a commercial motor vehicle is moving, as well as at specified engine power-up or shutdown, duty-status, and personal-use or yard-move events. That interval applies to ELD records as described in the FAQ; it is not a general telematics cadence.
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- [CUSTOM SAFETY & SECURITY ALERTS] Receive push notifications for speeding, vehicle movement, geofence entry or exit, and device disconnection. Use configurable alerts to monitor teen drivers, family vehicles, company cars, or potential theft.
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Do not assume that different systems report at the same frequency. As one research-fleet example—not an operating standard—the National Laboratory of the Rockies describes collecting in-use commercial-vehicle CAN diagnostics and GPS at 1 Hz (once per second). The source page does not state a publication year. The lab’s example includes location, speed, energy use, fuel use, and other vehicle functions.
Regulatory safety data also has a distinct purpose. FMCSA says its Safety Measurement System (SMS) uses roadside inspection and crash-report data from the prior two years, along with investigation data; it updates monthly and organizes information into seven BASIC categories. FMCSA cautions: “Readers should not draw conclusions about a carrier’s overall safety condition simply based on the data displayed in this system.” Treat SMS as a regulatory measure, not a complete picture of a carrier’s internal safety performance.
Check the data before using it to train or trigger decisions
A field that exists in a device specification may still be missing, inconsistent, delayed, or unavailable on some vehicles. Assess the stream across the actual fleet and over time before relying on it.
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- Coverage: Which vehicles report the field, and which are absent or intermittently connected?
- Meaning and units: Are units, event definitions, identifiers, and status values consistent across vehicle classes and systems?
- Time: Are timestamps accurate and time zones understood? Does the source cadence fit the decision being made?
- Linkage: Can records be reliably joined to the vehicle, trip, driver where appropriate, work order, or business outcome?
- Quality flags: Can the fleet distinguish a true zero from a missing reading, stale value, or device fault?
- Compatibility: Does the vehicle interface, OEM system, ELD, telematics device, or fleet-management platform expose the field in a usable format?
Set a quality threshold appropriate to the action. A low-confidence alert may be acceptable as a prompt for human review but not as the sole basis for taking a vehicle out of service or evaluating a driver.
Prioritize new data streams by their operational trade-offs
Use the same questions to compare a proposed field or device with what the fleet already collects. These are decision criteria, not a ranking established by federal sources.
- Decision value: What action could change if this data is available?
- Coverage and quality: How many vehicles report it, how often, and with what missingness, unit consistency, and timestamp accuracy?
- Context and linkage: Can the field be connected to the relevant vehicle, driver where appropriate, trip, work order, and outcome?
- Compatibility and integration: Can existing vehicle and fleet systems supply it in a usable format?
- Governance: Is collection necessary for the stated purpose? Who needs access, how long should it be kept, and how will drivers be informed?
- Cost and burden: What hardware, connectivity, integration, storage, review, and ongoing maintenance effort will it require?
More data does not automatically produce a better model. A narrowly scoped, consistent dataset with clear outcomes may be more useful than a larger set of poorly linked signals.
Set purpose and access rules for sensitive data
Location history and driver-linked events can reveal sensitive information about people and work patterns. Before collecting them, define the operational purpose, who can access the data, how long it is retained, and how drivers will be informed. Privacy, labor, surveillance, retention, and reporting requirements vary by jurisdiction and use; the federal sources described here do not establish a comprehensive rule set for all fleets. Have applicable counsel and labor requirements guide the fleet’s policies.
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