How enterprises can navigate the edge ecosystem



Formula 1 racing is the ultimate human-machine partnership. Every driver is like an engineer, making split-second decisions based on the data from over 200 sensors generating over 13,000 pieces of information. Although it’s the drivers piloting the vehicles around the race track, in a sport where performance is the puzzle and data is the key, it’s the engineers in the pit who are piecing it all together.

About the author

Arash Ghazanfari is CTO at Dell Technologies UK.

Few businesses epitomize the need for ‘edge computing’ quite as clearly as Formula 1. On an average race weekend, the McLaren team collects around 100 gigabytes of data on each car. They access the data in real-time, in the car, trackside and mission control. A spectator may feel like they’re in the heart of the action. But the engineers can see things like a gear change in the data before it’s heard on the track. Machine learning and analytics are constantly digging into that data and optimizing the performance of every component in the car to get the best racing results possible. And for those uninterested in fast cars, checkered flags and quick tire changes? The technology devised for the racetrack has far broader implications than one might imagine.

The body is an engine, and data is the fuel



Formula 1 racing is the ultimate human-machine partnership. Every driver is like an engineer, making split-second decisions based on the data from over 200 sensors generating over 13,000 pieces of information. Although it’s the drivers piloting the vehicles around the race track, in a sport where performance is the puzzle and data is the key, it’s the engineers in the pit who are piecing it all together.

About the author

Arash Ghazanfari is CTO at Dell Technologies UK.

Few businesses epitomize the need for ‘edge computing’ quite as clearly as Formula 1. On an average race weekend, the McLaren team collects around 100 gigabytes of data on each car. They access the data in real-time, in the car, trackside and mission control. A spectator may feel like they’re in the heart of the action. But the engineers can see things like a gear change in the data before it’s heard on the track. Machine learning and analytics are constantly digging into that data and optimizing the performance of every component in the car to get the best racing results possible. And for those uninterested in fast cars, checkered flags and quick tire changes? The technology devised for the racetrack has far broader implications than one might imagine.

The body is an engine, and data is the fuel

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