Resumen

HEREDIA, J.M.  y  AYALA, E.L.. IoT and AI-Based Predictive Maintenance System Design for Express Auto Repair Shops. Revista Técnica energía [online]. 2025, vol.21, n.2, pp.81-86. ISSN 2602-8492.  https://doi.org/10.37116/revistaenergia.v21.n2.2025.678.

The purpose of this document is to highlight the existing issue caused by a lack of knowledge about the actual condition of machinery and precise monitoring in an express mechanic workshop. This workshop consists of mechanical maintenance equipment such as vehicle lifts, balancers, aligners, and other common machinery in such work environments. The data collected from these machines are classified and processed using Artificial Intelligence, specifically Machine Learning, by employing a tabulation and interpretation algorithm alongside IoT (Internet of Things) through the instrumentation of these machines with sensors appropriate to their mechanical operation. This facilitates and enables the creation of predictive maintenance plans as well as operational schemes that help reduce operational costs, maintenance expenses, and energy consumption of the workshop equipment. The system innovatively uses a modular approach without requiring intervention or modification of the machines, allowing their interconnectivity with a computer that automatically manages the collected data. This results in a clear view of the usage of each component, providing critical information for generating predictive maintenance strategies.

Palabras clave : Optimization; IoT; Predictive Maintenance; Energy Savings; Artificial Intelligence..

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