Predict maintenance needs. Keep business moving.

Advancing fleet management through applied research and machine learning.

NAVARCHOS 3 builds on the NAVARCHOS 2 Fleet Management System to bring data-driven predictive maintenance and broader IoT device connectivity into fleet operations. The project aims to help businesses anticipate faults, reduce avoidable downtime and use maintenance resources more effectively.

Connect more devices. Bring fleet IoT data together through a flexible interoperability layer.
Spot issues early. Use machine learning to detect unusual patterns and emerging maintenance needs.
Make maintenance count. Use vehicle condition insights to reduce unnecessary service work.
Keep business moving. Act sooner to reduce unexpected downtime and help control operating costs.

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Concept illustration of connected fleet vehicles with IoT sensors, anomaly detection and predictive maintenance insights

Applied fleet intelligence

Connected vehicle data. More informed maintenance.

The project brings two complementary research priorities together: expanding access to fleet data and turning that data into practical predictive maintenance insights.

Predictive maintenance

The proposed predictive maintenance service combines data analytics, machine learning and anomaly detection to complement expert knowledge and periodic maintenance guidelines. Its goal is to identify emerging faults between scheduled checks and reduce unnecessary maintenance, helping fleets act before issues disrupt daily operations.

IoT interoperability

A dedicated interoperability layer is designed to extend the range of compatible fleet IoT devices. By making more vehicle data available across connected systems, the project aims to support broader adoption and provide a stronger foundation for data-driven fleet services.

Research into practice

Bringing Industry 4.0 innovation to fleet businesses

NAVARCHOS 3 explores how advances in data analytics, machine learning and distributed IoT and edge computing can support practical fleet maintenance services.

Connecting research and industry

The project brings together an academic research organization and a Cypriot SME with complementary expertise in predictive maintenance and fleet management. This collaboration supports knowledge exchange between academia and industry, strengthens local research and innovation, and aims to turn research outcomes into commercially useful services.

From validated technology to demonstration

Building on NAVARCHOS 2, funded under RIF-ENTERPRISES/0916/0072, the proposal takes anomaly detection and predictive maintenance technologies at Technology Readiness Levels (TRL) 4 to 5 toward a TRL 6+ demonstrator. The aim is to develop and test advanced fleet services that support business competitiveness and further digitization.

Project funding

Supported by RESTART 2016–2020

NAVARCHOS 3 is funded by the Research and Innovation Foundation through the RESTART 2016–2020 Programmes, under agreement ENTERPRISES/0521/0138.