Embedded systems control devices and have dedicated functions, while cyber-physical systems intensively connect computational entities to the physical world. The research group at Linnaeus University studies cyber-physical systems and IoT security, developing techniques for smart troubleshooting of connected devices and applying IoT solutions to smart environments. They also provide IoT education to help students learn about these important topics.

1. IoT research and
education at
Linnaeus University
Francesco Flammini, Ph.D.
Department of Computer Science and Media Technology
francesco.flammini@lnu.se
IoT tech day
August 29, 2019 – Kalmar, Sweden

2. ISO IoT Reference Architecture
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3. Embedded Systems & Cyber-Physical Systems
Embedded Systems (ES) are controllers with a dedicated function within a larger
mechanical or electrical system possibly with real-time computing constraints.
They are part of complete devices including hardware and mechanical parts.
Embedded systems control many devices in common use today.
Cyber-Physical Systems (CPS) are systems of collaborating computational entities
which are in intensive connection with the surrounding physical world and its on-
going processes, possibly using data-accessing and data-processing services
available on the Internet.
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Control
System
Sensor
System
Actuator
System
ENVIRONMENT
ES
CPS

4. CPS
IoT vs ES vs CPS
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IoT
ES
sensors
actuators

5. CPS Research Group
• https://lnu.se/en/research/searchresearch/cyber-
physical-systems-cps/
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6. Why security is so important
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7. The Internet of Ransomware Things…
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8. Some pointers to LNU IoT security research
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9. IoT Smart-Troubleshooting & Self-Healing
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Francesco Flammini, Mauro Caporuscio, Narges Khakpour, Prasannjeet Singh, Johan Thornadtsson (2019).
Smart-Troubleshooting Connected Devices: Concept, Challenges and Opportunities. Journal of Future
Generation of Computer Systems (Elsevier). To appear.

10. Other recent applications to smart environments
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Perez, D., Memeti, S., Pllana, S. (2018). A simulation study of a smart living
IoT solution for remote elderly care. 2018 Third International Conference on
Fog and Mobile Edge Computing (FMEC). 227-232.
Alsouda, Y., Pllana, S., Kurti, A. (2018). A Machine Learning Driven IoT
Solution for Noise Classification in Smart Cities. Machine Learning Driven
Technologies and Architectures for Intelligent Internet of Things (ML-IoT),
August 28, 2018, Prague, Czech Republic. 1-6.
Papp, J., Tokody, D., Flammini, F. (2018). From traditional manufacturing
and automation systems to holonic intelligent systems. Procedia
Manufacturing. 931-935.

11. IoT education
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12. Thank you for your kind attention!