Reducing energy consumption is a major concern for politicians in both the US and Europe, and Big Data has a huge role to play in this process.
The last few months have brought various announcements in this area.
There is speculation that Big Data firms are about to enter into partnerships with the Department of Energy in the US, and the application of Big Data and machine learning techniques to wind energy data continues to increase in sophistication.
Despite these advances, however, there remain two primary areas in which Big Data is helping to track and reduce energy consumption.
One is the pioneering work being undertaken in “smart cities” in both the US and Europe.
The second is the increase in the number of apps that allow consumers to track their own energy consumption.
In this article, we’ll take a look at both, and then point to some of the challenges that will need to be overcome before these initiatives go mainstream.
googletag.
cmd.
push(function() { googletag.
display(div-gpt-ad-1439400881943-0); }); Smart Cities Smart cities are leading the way when it comes to reducing energy consumption via the use of Big Data.
To date, the most impressive success stories have come from the US, where the proximity of tech companies and local governments has created a fruitful environment for collaborative working.
One of the most impressive initiatives to date has been pursued by Envision America, a non-profit organization that aims to encourage cities across the US to implement Big Data analytics in order to achieve social, environmental, and economic benefits.
A few years ago, the nonprofit rolled out its first energy initiative along with the city of Charlotte, UNC Charlotte, Duke Energy, and local businesses.
The aim was to help Charlotte’s biggest buildings in the city center curb energy consumption by 20%.
This project was ambitious both in scope and expected outcome.
Envision had to overcome the concerns of many companies over sharing commercially sensitive data with both their competitors and the public, which they did by installing encrypted cloud storage and top-line VPN services across the city.
Eventually, though, it was the employees of these companies who made the biggest difference: merely having data on energy consumption available meant that many staff turned down their thermostats and unplugged equipment they were not using.
In the end, the program achieved a 17.
2% reduction in energy use.
Phone Apps The second major area of progress in using Big Data to reduce energy use is coming at the other end of the spectrum.
Rather than tracking the energy consumption of entire cities, a variety of tech startups are building apps that allow consumers to track their own energy consumption.
Apps like this are leveraging a widespread shift in consumer attitudes.
Being able to access data on personal energy consumption is certainly attractive to an increasing number of people, but many of these tech startups also hope that this can act as a catalyst to a more widespread change.
Companies are increasingly putting their commitment to the environment at the forefront of their customer offer, and the energy used in computationally expensive processes.
like payment processing and encryption, are a major focus of research for many of them.
Ultimately, the goal of energy consumption apps is not just to track individual environmental impact, but to integrate this data acquisition into wider networks that are able to assess the impact of consumer and business decisions.
Whether that goal will be achieved, however, is contingent on overcoming some of the issues that have plagued Big Data systems.
When Data is Not Enough In order for Big Data to contribute to reducing energy consumption, two huge challenges will have to be overcome.
These are concerns over the security of data acquisition systems, and the still inadequate ability to analyze the huge amount of data that they produce.
Given the track record of city governments when it comes to keeping personal data safe, many have concerns that allowing them to collect more data from citizens and businesses is a disaster waiting to happen.
As complex networks get harder to secure, local governments will have to increase their security infrastructure at the same rate that they increase their ability to monitor energy consumption.
Whilst the rise of DevSecOps and increased IoT security can contribute to making these systems more secure at a technical level, a shift in mindset will also be required.
Instead of governments collecting data just because they can, they will need to think carefully about exactly which data are required to achieve their goals and to put in place proper protection for this information.
Secondly, the ability to analyze energy consumption data still lags well behind the ability to collect it.
If a particular building is consuming more energy than others in the neighborhood, this is easy enough to see even through a basic analysis.
The critical question, however, is one of what can be done about this.
AI-driven analysis tools may soon be able to trawl through the huge amounts of data required generated by IoT sensor networks, but to date, these systems remain underutilized even in smart city initiatives.
The Bottom Line If these challenges can be overcome, however, the future of big data in the energy industry is bright.
Reducing energy consumption is a win-win situation for both companies and consumers, lowering costs as well as limiting environmental impact.
What will be key, in the coming decade, is for the currently discrete streams of research in this area to be united.
Smart cities will need to start sharing data with consumers, and consumers will need to start feeding data on their personal energy consumption into the city- or nationwide schemes.
If that can be achieved, then Big Data techniques will become a critical tool in reducing energy consumption.
About the Author Gary Stevens is a front end developer.
He’s a full time blockchain geek and a volunteer working for the Ethereum foundation as well as an active Github contributor.
Sign up for the free insideBIGDATA newsletter.
.