Energy At The Edge

How much energy will billions of complex devices require?

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Ever since the first mention of the IoT, everyone assumed there would be billions of highly efficient battery-powered devices that drew milliwatts of energy. As it turns out, we are about to head down a rather different path.

The enormous amount of data that will be gathered by sensors everywhere cannot possibly be sent to the cloud for processing. The existing infrastructure cannot handle it, and there are doubts that even 5G using millimeter-wave technology would suffice. This realization, which has become a hot topic of discussion across the electronics industry in the past few months, has broad implications.

Rather than a collection of dumb, simple, mass-produced sensors, edge devices will have to be much more sophisticated and do far more processing than previously thought. They will need to assess which data should be relayed to data centers, which data should be stored locally, and which data can be thrown away.

These are complex transactions by any metric. Data types vary greatly. Vision data is different from voice data, which is different again from data about mechanical vibration or near-field scans from an industrial or commercial operation. Understanding how data can be used, and what is useful within that data, requires sophisticated collection, partitioning and purging, which is the kind of stuff that today is being done by very powerful computers.

How this affects electricity usage on a global scale remains to be seen. Most reports show the total energy consumption is expected to continue increasing steadily, particularly in countries outside the Organization for Economic Cooperation and Development, which roughly includes North America, Europe, Japan and Australia.


Fig. 1: Relatively steady energy consumption projections. Source: U.S. Energy Information Administration

The problem is that most reports are outdated when it comes to predicting energy consumption. A few months can make a huge difference when it comes to fundamental shifts in where processing will be done. Most reports either extrapolate from existing data and population growth, or they focus on specific market activity and growth in smart phone and tablet sales, which has been flattening. In fact, the most recent reports available show a fairly steady growth in overall Internet traffic.


Fig. 2: Steady Internet growth projections. Source: Cisco VNI, 2017

This is beginning to change, however. A recent Cisco report (see Fig. 2, above) projected a 46% increase in mobile data. This is the nexus of more data collected from more sensors and processed in multiple stages, which ultimately will impact energy consumption on a mass scale. This is no longer just about the number of smart phone customers. It’s a combination of people, devices, and machines talking to machines.

A Cowen & Co. report issued last year provided another reference point. It focused on the amount of data generated by connected cars, based upon research from Gartner. The report, published in Barrons, is just one slice of the rising amount of data being collected across all markets (see Fig. 3, below). Note the increase between 2019 and 2020 in the automotive market.


Fig. 3: Volume of data generated by connected cars each year, in petabytes. Source: Cowen/Gartner.

Some of this will be absorbed by an increase in renewable energy production, particularly wind and solar power. Some of it also will be handled by more efficient processing and new chip architectures, which is excellent news for the semiconductor and EDA sectors. But it will still have a big impact a power grid that already is being stretched worldwide, which in turn could drive up the price of energy to charge these devices.

So far, there is far too little data about how all of these pieces will fit together, and no collective projection about how billions or tens of billions of sophisticated edge devices will impact the world’s power grid. The best we can do today is cobble together pieces of reports from different market segments and make extrapolations, which is not an ideal state of affairs. Because everything is increasingly connected, problems in one area can have far reaching implications for other areas. It would be extremely helpful to the entire industry to be able to predict and prepare for that.

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