How edge computing is advancing sustainability across industries

A person standing in front of a rack of servers inside a data center
(Image credit: / Gorodenkoff)

Technology is supercharging sustainability as companies around the world evolve their strategies to drive energy efficiency and reduce their environmental impact. Enterprises often look to cloud migration, smart data practices and, increasingly, AI-powered capabilities for support in achieving their sustainability goals. But there’s an additional opportunity that enterprises should consider as part of their environmental strategies: capitalizing on edge computing as a sustainability asset.

The evolution of edge computing has enabled real-time data processing and rapid decision making in numerous industries. Through edge computing advances, including the ability to deploy AI-tools and machine learning at the edge, healthcare providers can access real-time patient data, retailers can strengthen loss prevention and manufacturers can drive the convergence of IT with operational technology (OT) for seamless communication in industrial settings.

Leaders in heavily regulated industries depend on edge computing for enhanced security and data protection, and they benefit from the lower latency and reduced costs that result from processing data closer to where it’s generated. As they drive broader business goals, these enterprises can also apply edge computing — supported by innovations in AI and machine learning, 5G connectivity and IoT devices — to optimize their energy use and waste, identify more sustainable practices and maximize the utility of valuable resources.

For example, edge computing can enable data analysis from IoT devices in manufacturing plants. And by using dashboard visualization, companies can better understand their energy use and even adjust their facilities’ power draw in real time. Edge computing also supports industrial sustainability efforts through smart grid applications that optimize efficiency and enable rapid responses to shifting energy demands.

Enterprises should adopt a thoughtful approach to edge computing that balances technology adoption with associated energy use and harnesses edge to integrate renewable energy sources. But as enterprises increasingly recognize the business value of applying edge technology — a March 2024 IDC forecast indicates that global edge computing investments will reach $232 billion by the end of this year, and reach nearly $350 billion in 2027 — they should also recognize that sustainable aims can be part of this value.

Here are three ways edge computing can help companies advance their environmental initiatives, navigate an evolving regulatory landscape and create new value through sustainability investment:

Steve Currie

Vice President, Global Network & Edge Compute and Distinguished Engineer, Kyndryl.

Enhancing sustainable practices with predictive maintenance

Employing predictive maintenance to conserve energy and resources is among the most powerful uses of edge computing, which can enable businesses to gain actionable insights from unstructured data. Predictive maintenance can help companies avoid equipment failures, maintain business continuity and reduce emissions and costs associated with service trips.

Predictive maintenance can be particularly helpful in remote locations, which can be difficult to reach for service. In one example, intelligent predictive maintenance supported by edge computing was demonstrated to improve the safety and performance of hard-to-access wind farms.

Relying on renewable energy sources will be critical to limiting global temperature rise and worsening climate impacts. But wind turbines are susceptible to fires, which can lead to costly repairs and increase the risk of wildfires and other ecological damage. Edge computing can potentially help address this risk through a solution that brings together edge technology, a thermal camera and a machine learning algorithm to analyze images and identify abnormalities. With the solution, wind turbines can be monitored in real-time, and operations can be shut down automatically without human intervention.

Processing this volume of data reliably for immediate decision making would be a major challenge without edge computing. Instead, operators can use this technology to manage assets proactively and help enable a more sustainable future.

Cutting back on landfill scrap

Edge computing can also be a valuable tool to enable the real-time processing that optimizes resource consumption, reduces defects and improves logistics.

In manufacturing settings, enterprises can reduce industrial waste and maximize the longevity of assets and equipment by employing predictive maintenance to strategically service and replace components. Edge computing also can support applications of AI-powered computer vision to spot costly defects in the production line. This curbs the fabrication of defective components that end up in landfills and combustion facilities, which produce greenhouse gas emissions.

Edge computing can also play a key role in optimizing resources in the retail industry. Retailers face challenges that include inventory and supply chain management, and they need to be able to monitor and analyze their inventory and rapidly adjust to supply chain disruptions and changing consumer demands.

Through applications of edge computing, retailers can assess their inventory in real time and place soon-to-expire items on sale, reducing the number of unsold products that are thrown away. Retailers can also apply edge computing and machine learning to predict demand trends for more accurate, less wasteful and less costly ordering.

Driving decision making with digital twins

A digital twin — supported by edge computing — uses data to create a simulated version of an object or process, enabling businesses to test situations and tailor their real-life decision making accordingly. Edge computing-based digital twin technology is being applied in multiple industries for a range of uses — from informing product designs that are more sustainable to improving the service delivery of energy providers.

An impactful example involving digital twins can be found in water treatment plants. These facilities must monitor their physical systems and energy use, and access to real-time insights on their operational performance can make plants more efficient. By building a digital twin, plant operators can simulate water quality parameters, water and air flows, and conditions related to the aeration process. They can then optimize and reduce energy consumption related to air flow and gain predictive maintenance insights to improve their operations.

Applying and benefitting from digital twin technology, and edge computing more broadly, requires industry expertise and deep technical skillsets across multiple technologies. Enterprises must also consider edge computing’s role in their sustainability goals and how to maximize its potential. Technology experts can help enterprises navigate these questions and manage the heavy lifting so companies can make the most of their edge investments.

However enterprises choose to advance their strategies and as they consider how they can contribute to the global effort that will be required to address climate change, there’s one certainty: it’s worth bringing sustainability to the forefront of their edge computing conversations.


This article was produced as part of TechRadarPro's Expert Insights channel where we feature the best and brightest minds in the technology industry today. The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here:

Steve Currie, Vice President, Global Network & Edge Compute and Distinguished Engineer, Kyndryl.