Artificial Intelligence of Things for Next-Generation Predictive Maintenance
Taimia Bitam, Aya Yahiaoui, Djallel Eddine Boubiche, Rafael Martínez-Peláez, Homero Toral-Cruz, Pablo Velarde-Alvarado, Paul Davidsson · 2025
Read Artificial Intelligence of Things for Next-Generation Predictive Maintenance by Taimia Bitam, Aya Yahiaoui, Djallel Eddine Boubiche, Rafael Martínez-Peláez, Homero Toral-Cruz, Pablo Velarde-Alvarado, Paul Davidsson (2025) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-12737171.txt.
Description
Taimia Bitam and co-authors review how AI linked with smart sensors is changing predictive maintenance, the work of fixing machines before they break. The shift fits Industry 5.0, which aims for plants that put people first, waste less, and bounce back from shocks. Old upkeep plans react after a failure or follow fixed timetables. Live sensor data, read by models that learn, can spot faults early and judge how much life a part has left.
The review builds a single scheme for the field: the AI models, the sensor networks, and the system designs in use. It covers plants, transport, and energy plants. It also weighs newer ideas: splitting work between edge devices and the cloud, training models without pooling private data, self-taught models, and digital twins of real machines. Strengths, weak points, and shared hurdles are drawn together.
Catalog record
| CREATOR | Taimia Bitam, Aya Yahiaoui, Djallel Eddine Boubiche, Rafael Martínez-Peláez, Homero Toral-Cruz, Pablo Velarde-Alvarado, Paul Davidsson |
|---|---|
| YEAR | 2025 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 212 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |