Connected Car Data for
Gain new insights by applying big data algorithms to vehicle health indicators
Advanced statistical analysis of historical car data can help predict when a part needs replacement or a vehicle needs service. Otonomo provides predictive maintenance software applications with clean, harmonized data from connected cars representing many makes and models. Our Automotive Data Services Platform makes it faster and easier for these applications to harness the power of connected car data as a big data source.
Ready to try our connected car data in your predictive maintenance software application?
Get better coverage with data from multiple OEM and fleet sources accessible through a single interface with a standards-based API.
Enriched Car Data
We apply patented technology to aggregate, cleanse, and enrich data, so you can focus on building better predictive algorithms.
Dynamic Blurring Engine
Protect driver privacy through dynamically de-identifying data while preserving its usability for predictive maintenance.
Predictive Maintenance Applications Can Use Connected Car Data for:
Trouble Code Analysis
Access a near real-time stream of diagnostic codes generated by vehicle engines.
Additional Vehicle Health Indicators
Capture multiple vehicle health indicators, such as mileage, fuel level, tire pressure, ambient air temperature, oil temperature, engine temperature, or RPM, to enable more sophisticated correlations.
Predictive Maintenance App for Consumers
Create a consumer-facing app for predictive maintenance with an end-to-end consent management flow for accessing personal data. Facilitate regulatory compliance and build consumer trust.
Accelerate responses to assistance requests with location data, as well as insights from diagnostic codes or other data generated by connected cars. Prioritize requests based on location or number of passengers in the car.
Optimize maintenance packages offered to vehicle owners based on the actual condition of the car. Integrate vehicle health data into existing systems.