APM - Advanced solution helping corporate and public transport fleets cut costs, boost efficiency and ensure service continuity through IoT, data and AI.
The APM – Automotive Predictive Maintenance project aims to introduce a new model for the intelligent management of corporate fleets and local public transport, addressing a gap that is still present in the Italian market.
The initiative aims to develop a predictive maintenance platform based on the continuous analysis of vehicle data collected through IoT devices integrated into automotive control units.
The solution leverages Machine Learning algorithms trained on high‑frequency datasets to anticipate failures, assess component degradation and optimise maintenance planning. As managed data volumes grow, the solution’s architecture evolves into a Big Data model designed to support increasing workloads and advanced analytical processes.
Beyond operational benefits, APM contributes to lower fuel consumption and reduced emissions through more efficient vehicle utilisation and optimised fleet management.
The main research directions include:
- advanced AI technologies, such as unsupervised ML, human‑in‑the‑loop approaches, data efficiency, and enhanced H2M/M2M;
- interactions human‑centric AI solutions to support decision-making competence;
- development and collaborative research within an open, European‑wide innovation framework;
- AI‑ready platforms, including algorithms, data repositories, autonomous systems and software components for IoT ecosystems.
Fincons is taking part in this project, co funded under the “Accordi per l’innovazione – Secondo sportello” framework established by the Ministerial Decrees of 31 December 2021 and 18 March 2022 of the Ministry of Enterprises and Made in Italy, together with ATON IT and the scientific partners Sapienza University of Rome and the University of Milano Bicocca.