Alberto Macii

Papers

Total Citations

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About

Alberto Macii is a leading figure in the fields of fog computing, predictive maintenance, and cyber-physical systems, with a particular focus on cloud-to-edge architectures for industrial analytics. His major contributions center on developing scalable, real-time data management and processing frameworks that enable predictive analytics in complex, distributed environments. By bridging the gap between cloud resources and edge devices, Macii’s work empowers industries to uncover hidden process insights, detect critical anomalies, and forecast imminent failures before they occur. This proactive approach—moving beyond reactive maintenance—has significant implications for operational efficiency and cost reduction. His most-cited papers, including "A Fog Computing Approach for Predictive Maintenance" (2019, 17 citations) and "A Cloud-to-edge Architecture for Predictive Analytics" (2019, 11 citations), are foundational in demonstrating how fog and edge computing can transform raw sensor data into actionable intelligence. Macii’s research is highly influential among engineers and data scientists seeking to implement robust, low-latency predictive systems in manufacturing, energy, and infrastructure. His work not only advances theoretical understanding but also provides practical, deployable solutions for the next generation of smart, self-optimizing industrial environments.