40 million data points from 4,000 data streams delivered via Device Cloud to analyze environmental data.
Digi International will take part in deploying over 500 sensor nodes at Google’s developer conference, Google I/O, May 15-17. The Data Sensing Lab project demonstrates how real-time machine-to-machine (M2M) data can provide insight into customer behaviors and preferences. Utilizing Digi’s XBee ZigBee modules and ConnectPort wireless gateways to connect the nodes, sensor data is then collected and managed via Device Cloud by Etherios, Digi’s platform for managing large populations of devices and connecting devices to applications.
“Google is using the Internet of Things to get a global view of their entire multi-million dollar event as it plays out in real time. They’re learning where people are going and when, how loud the applause is for each presentation, where it’s figuratively hot and where it’s literally cool.”
Rob Faludi, collaborative strategy leader at Digi International and member of the Data Sensing Lab team, said:
“But they’re also learning how easy it is to integrate M2M data, via Device Cloud’s APIs, with their own cloud-based business systems.”
“Google and Digi collaborated to create a complete end-to-end solution in just a few weeks, one that’s ready to hand us 40 million fascinating data points.”
The sensor network’s 4,000 data streams running over Device Cloud utilizes over 500 XBee modules connecting Arduino based sensors to provide continuous updates on temperature, pressure, light, air quality, motion and noise levels in San Francisco’s Moscone Center during the conference. The Google Cloud Platform team will gather, transform, and analyze the information, then share heat maps and other data visualizations in collaboration with the Google Maps team.
The Data Sensing Lab crew, Alasdair Allan of Babilim Light Industries, Kipp Bradford of Kippworks, Rob Faludi of Digi International, Michael Manoochehri, Amy Unruh and Kim Cameron of Google and Julie Steele of O’Reilly Media, created the project to collect data to answer questions about the physical world in a fun and awe-inspiring way.