Empowering Efficiency: Edge Computing’s Impact on Sustainability 

Picture your morning commute: you are navigating the bustling city streets on the way to your office. The traffic lights are dynamically changing based on the current traffic volume. Surveillance cameras monitor the intersections, sending real-time information to authorities to immediately reroute traffic in the event of an accident or stalled car. You may not realize it, but edge computing is powering your commute by minimizing congestion, reducing travel times, and enhancing safety. 

Edge computing refers to the practice of processing, storing, and analyzing data near the source of that data instead of sending it to a centralized cloud server or data center. This process helps to reduce latency, enhance efficiency, and improve performance by analyzing the data closer to where it is produced. As is seen in the example above, real-time processing of road conditions is critical to keeping traffic flowing seamlessly. With edge computing, that processing happens locally, speeding up the decision-making process and improving your commute. 

Edge computing is also advantageous in the retail, manufacturing, and healthcare fields, among others, and has become increasingly utilized with the proliferation of the Internet of Things items like smartwatches, Fitbits, and your Alexa. Because consumers today want their smart devices to provide quick information, edge computing is used to immediately meet the users’ demands.  

Edge Computing vs. Cloud Computing 

Edge and cloud computing are complementary functions that each have their unique strengths. Edge computing is most often used for situations that require real-time processing, like the Internet of Things, smart cities, and industrial automation, while cloud computing is ideal for projects requiring vast storage, heavy computation, and accessibility from anywhere in the world.  

A major difference between the two technologies is the physical location of the processing. Edge computing is the better choice when speed, scalability, and reliability are priorities. By processing data inputs close to where they are being captured – that is, on the edge – actionable outputs will be able to guide decisions within milliseconds. If that same data was sent to the cloud for processing, there could be substantial delays while the data moves between locations. 

Data security is another major consideration when choosing between edge and cloud computing. The Harvard Business Review discusses many of the trade-offs implicit in dealing with information and privacy. Although it is tempting for a company to collect multiple data points on their customers and then mine that data indefinitely, that practice can violate privacy guidelines. 

According to this article, edge computing implements three critical design choices that help protect privacy: sufficiency, aggregation, and alteration. By collecting fewer data points, reporting them in aggregate, and altering personally identifiable information, edge computing aids companies in making data-driven decisions without running afoul of privacy laws. 

Often, the ideal solution to a computing project is to use a hybrid model, where the strengths of both cloud and edge systems are leveraged to create a custom solution. Autonomous cars use a hybrid system, as is illustrated in this article from The Enterprisers Project. Cloud computing is used to deliver software updates to vehicles overnight; however, when you are on the road and need to veer to avoid an obstacle, edge computing takes over, making the decision to turn your wheel in milliseconds. 

Edge Computing as a Sustainable Business Practice 

Utilization of edge computing is rapidly being implemented across the globe. Several factors have contributed to making this technology more accessible, including advancements in hardware, connectivity improvements, the creation of industry standards and enhanced security measures, and advancements in machine learning and AI.  

However, edge computing has also become an effective method of enhancing sustainability and combating climate change. According to the International Energy Agency, the large data centers that house cloud computers produce 1% of all greenhouse gas emissions, which are responsible for global warming and climate change.  

Because centralized data centers are designed to operate continuously, their maintenance requires a significant amount of energy as well as large amounts of water to cool the hardware. One way edge computing installations can be made more efficient than their larger counterparts is through using GPUs (graphic processing units) for edge set-ups instead of more carbon intensive CPUs. GPUs consume fewer gigawatts than CPUs do, resulting in energy savings.  

Edge data centers are also able to leverage locally available renewable energy sources. By investing in renewable energy to power the GPUs, lights, ventilation, and cooling systems, companies can significantly decrease greenhouse gas production from their edge set-ups, while benefitting from the other strengths of renewable energy.  

Another benefit of edge computing – monitoring real-time conditions – can result in huge sustainability gains. By monitoring inputs, outputs, and system reliability on the edge, companies can optimize their resources, reduce waste, decrease fuel consumption, and lower emissions.  

The New Stack takes a look at various applications of edge computing and their impact on the environment. Besides the examples of autonomous cars and traffic management systems that have already been discussed, edge computing is also being used in industries like healthcare, security, retail, manufacturing, clean energy, sustainable technology, agriculture, and farming, where they are benefitting companies by optimizing operations, increasing efficiency and reducing waste.  

Whether turning off the lights in an empty room or monitoring the usage of a city’s power grid, you can be assured that edge computing is at work to make your life both easier and more sustainable.