Artificial Intelligent Sensors at the core of Cyber-Physical-Systems

Dr. Danilo Pau, Dr. Valeria Tomaselli

Cyber-Physical Systems (CPS) are becoming, without pace, more pervasive into embedded systems. Artificial Intelligence, Machine Learning and Deep Learning are mostly confined into the cloud, where unlimited computing resources seems to be available and evolving tirelessly. Unfortunately a layered architecture in which dumb sensors are attached to the cloud would become quickly too centralized, poorly scalable and slowly responsive in the IoT expected scenario that will deploy hundreds of billions of sensors communicating through low data rate networks.
In that context, STMicroelectronics is developing solutions to bring Artificial Intelligence closer to the sensors and potentially within same package. This talk will review new intelligent technological solutions and mechanisms under development and publicly announced. The talk will tell how they represent the key ingredients needed to design the current and future generation of artificial intelligent cyber-physical embedded systems and derived applications based on STMicroelectronics heterogeneous sensors, micro controllers and SoCs. In particular, aspects related on how address current interoperability, productivity and constrained embedded resource gaps will be discussed with practical examples. Moreover, the investigation and design of adaptive and cognitive computational-intelligence techniques able to learn, adopting artificial neural networks, and operate in nonstationary environments will be introduced. Finally, the deployment of credible networked intelligent cyber-physical systems, able to operate in time varying environments, will be also disclosed.


Who we are
The Artificial Intelligent (Cyber-Physical) Sensor Revolution: from theory to practice
About Artificial Intelligence, Machine Learning and Deep Learning
Linear Algebra
Introduction to Neural Networks
Why Deep Neural Networks
Different topologies of Neural Networks
Recurrent Neural Networks
Quantization: a subset relevant to Deep Learning
Deep Learning Applications
Deep Learning Tools & Frameworks
A simple tutorial example introduction demo
Orlando SoC
Unsupervised Learning for STM32

Artificial Intelligent Sensors The core of Cyber Physical Systems from Theory to Practice

Deep Learning Applications

Introduction to Neural Networks

Why Deep Neural Networks

Deep Learning Tools and Frameworks