Synthetic program: 1. Introduction: the industry 4.0 paradigm. Production, exchange and management of data. The enabling technologies: robotics, internet of things, big data and analytics.
2. Industrial automation: current and future scenarios of automation. Process automation: the role of feedback control. Discrete automation: action sequencing. The Programmable Logic Controller. Real time systems.
3. Industrial robotics: basic concepts and examples. Selection of a robot based on the application. Elements of robot kinematics, motion planning and control. Tools for robot motion programming.
4. Collaborative robotics: advantages in human-robot collaboration. Safety standards. Examples and applications.
5. Introduction to Industrial Internet of Things (IIoT): building blocks and components.
6. Communication Technologies for IIot: overview of the reference technologies for interconnecting industrial devices and processes (WiFi, industrial Ethernet, ZigBee, ISA 100, WirelessHART, Field BUS, RFID).
7. Communication protocols for the IIoT: overview of the reference protocols to provide services in industrial enviornments (OPC UA, MQTT, HTTP and COAP).
8. Management Platforms for the IIoT: hands on activities with IoT prototyping platforms (NodeRed) and cloud-based management platforms.
9. Introduction to the architectures of modern data management systems.
10. Basics of data integration: model heterogeneity, semantic heterogeneity at the schema level, heterogeneity at the data level.
11. Dynamic data integration: the use of wrappers, mediators, meta-models, ontologies, , etc.
12. Introduction to data analysis and exploration.
Lecture Notes
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Live
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