Feasibility study exploring AI and machine learning applied to commercial-fleet telematics and driver feedback.
Overview
AIPTO was a six-month Innovate UK feasibility study examining whether AI and machine learning could be applied to commercial-fleet telematics data to support more targeted driver feedback and training. The project built on Hodos Media’s earlier Fleetfoot work and considered how individual driving patterns, operational context and other data could inform tailored improvement tasks.
Objective
To determine the feasibility and value of applying AI and machine learning to telematics data for more personalised and evidence-based driver feedback.
Work undertaken
The study covered stakeholder analysis, state-of-the-art review, user and technical requirements, AI and machine-learning feasibility, commercial feasibility and project planning, with input from fleet and telematics partners.
Outputs and findings
Outputs included stakeholder and market evidence, user and technical requirements, AI and machine-learning feasibility findings, commercial assessment and a defined route to a proof-of-concept phase. The study established sufficient technical and commercial basis for a more focused follow-on project centred on event-to-video integration and instructor-led training.
Contribution to Hodos Media
AIPTO is the first funded AI project in the current TaaSchen sequence and provides the feasibility baseline for FAIDA and FleetSkillAI.
Funding acknowledgement
This project was supported by Innovate UK.