Presented By O’Reilly and Cloudera
Make Data Work
March 5–6, 2018: Training
March 6–8, 2018: Tutorials & Conference
San Jose, CA

Pirelli Connesso: Where the road meets the cloud

Carlo Torniai (Pirelli Tyre)
4:20pm–5:00pm Wednesday, March 7, 2018
Big data and data science in the cloud, Data engineering and architecture
 Location: LL21 C/D

Who is this presentation for?

Big
  • Data architects, technologists, data scientists, hackers, and IoT practitioners

Prerequisite knowledge

  • A basic understanding of internet of things and cloud computing concepts and services

What you'll learn

  • Explore Pirelli Connesso, an IoT cloud-based system providing information on tire operating conditions, consumption, and maintenance

Description

Carlo Torniai shares the architectural challenges Pirelli faced in building Pirelli Connesso, an IoT cloud-based system providing information on tire operating conditions, consumption, and maintenance, and highlights the operative approaches that enabled the integration of contributions across cross-functional teams (vehicle dynamics, data science, infrastructure, digital product development, etc.).

Connesso uses a set of sensors mounted in a tire’s tread groove and an on-board sensor located in the inner wall of the tire that reports pressure, temperature, and load data to a receiver unit in the car, which in turn communicates with the smartphone app and the Pirelli cloud. The latter enables the system to store historical data to offer real-time analytics regarding tire consumption, residual mileage, maintenance status, and potential breakdowns. Connesso is at the heart of an ecosystem that links consumers to the sales centers. Using a geopositioning system, the app can locate the closest available workshop and directly book an appointment to have the pressure adjusted or the tires replaced.

Photo of Carlo Torniai

Carlo Torniai

Pirelli Tyre

Carlo Torniai is head of data science and analytics at Pirelli. An accomplished data scientist with experience ranging across various areas of computer science and information technology, Carlo has extensive experience in data modeling, data analysis, and data engineering, and Python in the data science space (e.g., pandas, scipy, scikit-learn). Previously, he was a staff data scientist at Tesla Motors. He holds a PhD in informatics from the Università degli Studi di Firenze, Italy.