How edge computing is driving sustainability across sectors

Technology is driving sustainability as businesses around the world evolve their strategies to increase energy efficiency and reduce their environmental impact. Companies often look to cloud migration, smart data practices and, increasingly, AI-powered capabilities to help achieve their sustainability goals. But there’s another opportunity that businesses should consider as part of their environmental strategies: leveraging edge computing as a sustainability tool.

The evolution of edge computing has enabled real-time data processing and rapid decision-making across many industries. Advances in edge computing, including the ability to deploy AI tools and machine learning at the edge, allow healthcare providers to access real-time patient data, retailers to strengthen loss prevention, and manufacturers to accelerate the convergence of IT with operational technology (OT ) stimulate. seamless communication in industrial environments.

Leaders in heavily regulated industries depend on edge computing for improved security and data protection, and they benefit from the lower latency and lower costs that come from processing data closer to where it is generated. As they pursue 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 consumption and waste, identify more sustainable practices and maximize the utility of valuable resources to maximize.

For example, edge computing can enable data analysis of IoT devices in manufacturing facilities. And by using dashboard visualization, companies can better understand their energy consumption and even adjust the power consumption of their facilities in real time. Edge computing also supports industrial sustainability efforts through smart grid applications that optimize efficiency and enable rapid responses to changing energy needs.

Companies must take a thoughtful approach to edge computing that balances technology adoption with associated energy consumption and leverages edge to integrate renewable energy sources. But as companies increasingly recognize the business value of adopting edge technology — a March 2024 IDC forecast indicates that global investment in edge computing will reach $232 billion by the end of this year and nearly $350 billion by 2027 — they must also recognize that sustainable goals can be part of this value.

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

Improving sustainable practices with predictive maintenance

Deploying predictive maintenance to save energy and resources is one of the most powerful uses of edge computing, helping companies gain actionable insights from unstructured data. With predictive maintenance, companies can prevent equipment failures, maintain business continuity, and reduce emissions and costs associated with maintenance.

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

Reliance on renewable energy sources will be crucial to limit global temperature rise and worsening climate impacts. But wind turbines are prone 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 combines edge technology, a thermal camera and a machine learning algorithm to analyze images and identify anomalies. The solution allows wind turbines to be monitored in real time and operations to be automatically shut down without human intervention.

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

Reducing waste in landfills

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

In manufacturing environments, companies can reduce industrial waste and maximize the life of assets and equipment by using predictive maintenance to strategically maintain and replace components. Edge computing can also support AI-driven computer vision applications to detect costly defects on the production line. This reduces the production of defective components that end up in landfills and incinerators, producing greenhouse gas emissions.

Edge computing can also play a key role in optimizing resources in retail. Retailers face inventory and supply chain management challenges. They need to be able to monitor and analyze their inventory and quickly adapt to supply chain disruptions and changing consumer demands.

Applications of edge computing allow retailers to 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 cheaper orders.

Boosting decision-making with digital twins

A digital twin — powered by edge computing — uses data to create a simulated version of an object or process, allowing companies to test situations and tailor their real-life decision-making accordingly. Edge computing-based digital twin technology is being deployed across multiple industries for a variety of purposes — from informing product designs that are more sustainable to improving energy supplier services.

An impressive example of digital twins can be found in water treatment plants. These facilities need to monitor their physical systems and energy consumption, and access to real-time insights into their operational performance can make factories 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 airflow and gain predictive maintenance insights to improve their operations.

Adopting and capitalizing on digital twin technology, and edge computing more broadly, requires industry expertise and deep technical skills across multiple technologies. Companies must also consider the role of edge computing in their sustainability goals and how to maximize its potential. Technology experts can help companies answer these questions and manage the heavy lifting so that companies can get the most out of their edge investments.

However companies shape their strategies and how they can contribute to the global effort needed to address climate change, one thing is for sure: it pays to put sustainability at the forefront of their conversations about edge computing.

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