{"id":16645,"date":"2026-01-15T10:26:52","date_gmt":"2026-01-15T09:26:52","guid":{"rendered":"https:\/\/it-u.at\/?p=16645"},"modified":"2026-01-15T10:29:10","modified_gmt":"2026-01-15T09:29:10","slug":"network-spotlight-from-sensors-to-intelligence-building-the-future-of-edge-and-physical-ai","status":"publish","type":"post","link":"https:\/\/it-u.at\/en\/news\/network-spotlight-from-sensors-to-intelligence-building-the-future-of-edge-and-physical-ai\/","title":{"rendered":"Network Spotlight – From Sensors to Intelligence: Building the Future of Edge and Physical AI"},"content":{"rendered":"\n

The latest Network Spotlight at IT:U \u2013 Interdisciplinary Transformation University Austria focused on how intelligence is moving from centralized cloud systems into the physical world. Fellow Professor Michele Magno<\/a> presented his keynote, From Sensors to Intelligence<\/em>, highlighting how Edge and Physical AI enable systems to sense, process, and act directly where data is generated.<\/em><\/em><\/p>\n\n\n\n

From Sensors to Intelligence<\/h3>\n\n\n\n

In his keynote, Prof. Magno introduced the emerging field of Edge and Physical AI, which brings intelligence directly to devices operating in the real world. Rather than relying on centralized cloud computing, these systems process data locally, reducing energy consumption, latency, and dependency on constant connectivity.<\/p>\n\n\n\n

His research at the Smart Sensing Systems Laboratory (S\u00b3Lab) <\/a>bridges hardware design, efficient AI, and communication technologies to create systems that are energy-aware, context-adaptive, and designed around human needs. This interdisciplinary approach enables intelligent behavior at the edge, where sensing, decision-making, and action happen in real time.<\/p>\n\n\n\n

Where Research Meets Education<\/h3>\n\n\n\n

A central theme of the talk was the close integration of research and education. Prof. Magno highlighted how project-based learning (PBL) is embedded directly into research activities at IT:U. Students do not only study concepts but actively design, build, and test real systems, from low-level sensors to fully functional intelligent prototypes. This hands-on approach accelerates innovation while preparing students to think across disciplines, combining engineering, AI, and system-level thinking to address real-world challenges.<\/a><\/p>\n\n\n\n

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\u201cTechnology education must evolve with technology itself. Through Physical AI and project-based learning, we merge research and teaching, enabling students to design, build, and understand intelligent systems that interact with the real world. This fusion of edge intelligence and experiential learning prepares a new generation of innovators ready to tackle societal challenges with creativity, responsibility, and purpose.\u201d<\/em><\/em><\/p>\nMichele Magno, IT:U Fellow Professor of Embedded Systems & Edge AI\u202f<\/cite><\/blockquote>\n\n\n\n

From Theory to Real-Life Applications<\/h3>\n\n\n\n

Prof. Magno presented several concrete project examples that demonstrate how Edge and Physical AI translates into impact:<\/p>\n\n\n\n