Type of course:
Live session
Language:
IT
Duration:
8 hours
Proficiency:
Beginner
Target:
Professionals
The “Business Meets Innovation” training series, developed by EIT Manufacturing in collaboration with the Collège des Ingénieurs, helps professionals understand how emerging technologies — such as Artificial Intelligence, collaborative robotics, and Extended Reality — can transform industrial and business processes.
Through interactive sessions, real-world case studies, and direct engagement with startups and experts, participants will learn how to translate technological potential into concrete innovation within their organizations.
This session explores how Extended Reality (XR) and Artificial Intelligence (AI) are transforming quality control processes.
Docente
Fabio Poiesi, Head of Technologies of Vision, Fondazione Bruno Kessler
Founders and Startups
Alessandro Zara, Exvirience
Roberto Mangano, Fifth Ingenium
Alessandro Lavelli, ML cube
Simone Iannucci, Francesco Solinas, Olorin
Tech 4 Business – XR e AI per il Controllo Qualità - Training session
On-site | Workshop | November 19, 2025 | Piazza San Carlo 206, Torino (TO), Italy | Time 14:30 - 18:30 Duration: 4 hours Location: Collège des IngénieursLearning outcomes
- Understand how XR and AI technologies enhance precision and efficiency in quality control.
- Evaluate practical applications of vision systems, data analytics, and immersive environments.
- Design approaches for integrating AI and XR into existing quality management processes.
Topics
Uncategorized
Provided by
-
EIT Manufacturing – IC South
-
CDI – Collège des Ingénieurs
+13
enrolled
Course Includes
- 1 Certificate of achievement
Other editions
Related
-
IntermediateCircularity and Information Sharing for Resilient Value Chains
By Faculty of Engineering of University of PortoThis lesson explores strategies for creating circular, sustainable value chains, emphasizing the importance of information sharing and collaboration to build resilience, particularly in critical sectors like automotive and electronics.
Digital learning, Lesson- Quiz1
-
IntermediateAugmenting Workers
By Faculty of Engineering of University of PortoThis lesson discusses technologies that enhance human capabilities in the workplace, such as exoskeletons and augmented reality, empowering workers to perform complex tasks more efficiently and safely.
Digital learning, Lesson- Quiz1
-
IntermediateHuman-Robot Collaboration for Assembly/Disassembly
By Faculty of Engineering of University of PortoThis lesson examines the integration of COBOTs (collaborative robots) in industrial processes, explaining how humans and robots can safely and efficiently work together in tasks like assembly and disassembly.
Digital learning, Lesson- Quiz1
-
IntermediateData Analytics for Energy Efficiency and Sustainability
By Faculty of Engineering of University of PortoThis lesson focuses on using real-time data analytics to optimize energy usage in industrial settings, reducing waste, and improving sustainability through smart energy management systems.
Digital learning, Lesson- Quiz1
-
IntermediateDigital Technologies Enabling Industry 5.0
By Faculty of Engineering of University of PortoThis lesson introduces key digital technologies driving Industry 5.0, such as AI, IoT, and cobotics, highlighting how they enhance efficiency, sustainability, and human-machine collaboration.
Digital learning, Lesson- Quiz1
-
IntermediateIntroduction to Industry 5.0
By Faculty of Engineering of University of PortoThis lesson explores the evolution from Industry 4.0 to Industry 5.0, emphasizing human-centric, sustainable, and resilient manufacturing systems, where humans and advanced technologies co-create value.
Digital learning, Lesson- Quiz1
-
IntermediateIndustry 5.0: Transition to Sustainable, Human-Centric and Resilient Manufacturing
By Faculty of Engineering of University of PortoThis course explores the evolution from Industry 4.0 to Industry 5.0, highlighting the shift towards sustainable, human-centric, and resilient manufacturing practices. Learners will gain a comprehensive understanding of Industry 5.0 fundamentals, focusing on its core principles and distinct differences from previous industrial revolutions. The course delves into the integration of advanced digital technologies, such as real-time data analytics and automation, to enhance energy efficiency and operational sustainability in industrial settings. Participants will learn to identify inefficiencies and propose value-driven improvements. Additionally, the course covers the application of human-robot collaborative systems, emphasizing intelligent collaborative cells that facilitate safe and efficient human-robot interaction, thereby contributing to enhanced resilience in manufacturing processes.
Digital learning, Path- Course Certificate
49 € -
IntermediateAugmented Reality Application Development for Equipment Health Monitoring
By Laboratory for Manufacturing Systems and Automation of Patras - Laboratory for Manufacturing Systems and Automation of PatrasThis lesson teaches learners how to design Augmented Reality (AR) applications for monitoring equipment health. They will learn to formulate microservices for AR-based monitoring, create data monitoring and visualization workflows, and develop AR modules that provide real-time monitoring of equipment performance.
Digital learning, Lesson -
IntermediateIntroduction to MQTT
By Beia Consult InternationalMessage Queuing Telemetry Transport (MQTT) is a lightweight messaging protocol for Internet of Things (IoT), using a publish/subscribe model for efficient, real-time communication. Common uses include smart homes, industrial automation, and environmental monitoring.
Digital learning, Lesson- Quiz1
-
IntermediateIntroduction to Time Series Databases
By Beia Consult InternationalTime Series Databases (TSDBs) efficiently store and retrieve time-stamped data for applications like IoT, monitoring, and finance. They come in SQL-based (e.g., MySQL, PostgreSQL) for structured queries and NoSQL-based (e.g., InfluxDB, MongoDB) for scalability and high-velocity data handling. The choice depends on data volume, query complexity, and scalability needs.
Digital learning, Lesson- Quiz1