Machine learning and the Internet-of-Things are combining to create more intelligent cyber-physical systems. By moving intelligent processing closer to data generation units, these systems can increase autonomy, reduce decision-making latency, lower transmission bandwidth usage, and improve energy efficiency. Bringing together novel machine learning theories with innovative hardware and embedded device solutions is enabling the development of intelligent IoT and cyber-physical systems that can handle complex systems and human interaction.

1. Machine Learning and
Internet-of-Things: opposites
attract in the age of data
Prof. M. Roveri
Dipartimento di Elettronica, Informazione e Bioingegneria
Politecnico di Milano, Italy
Data Driven Innovation 2018 - Roma

2. Towards Intelligent Cyber-physical Systems
Physical
Domain
Cyber
Domain
Object
Domain
Physical
Sensing
Actuation
and Control

3. Towards Intelligent Cyber-physical Systems
Physical
Domain
Object
Domain
 Increase autonomy
 Reduce decision-making latency
 Reduce transmission bandwidth
 Increase energy-efficiency
Move intelligent processing as close as possible
to data generation units

4. Novel Theory in
the field of
Machine
Learning
Novel Solutions
in the field of
Hardware and
Embedded
devices
Intelligent IoT and
Cyber-Physical
Systems

6. “Complex systems and human-in-the-loop”

7. “Hardware is not a commodity”
New York Times
May 26, 2016

8. IEEE Spectrum
Aug, 2016
“From the Lab to the Real-world…”

9. “Somebody is Listening…”

10. “The Dark Side of the Moon”

11. Data Driven Innovation 2018 - Roma