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Environmental sustainability is one of the most urgent topics today. If we want to stabilize the earth’s climate, protect our ecosystems, and preserve natural resources for the future, society must take the move to sustainable operations seriously.

There’s pressure on all fronts. Regulatory compliance, financial markets, company brand, cost control, and even acquisition of talent are creating this sense of urgency. That’s why you see aggressive goals for businesses, cities, educational institutions, and others to reach net-zero operations in the coming years. Organizations of all types and sizes are building eco-conscious initiatives at the core of their operating model.

But it’s a steep path in getting there, and IoT technology offers a step forward. Organizations are transforming their operations through innovations in AI, machine learning, and computer vision platforms—increasing agility, productivity, and profitability. And by doing so, they are also paving the way to carbon-neutral operations.

The Growing Business Case for Sustainable Operations

When businesses move to more sustainable operations, it’s not just the environment that benefits but the economic payback and new business opportunities that come along with these changes. The manufacturing segment is one case in point. In addition to addressing the climate change challenge, optimized use of resources like energy and raw materials can lead to cost savings.

Optimizing operations with industrial #IoT solutions can improve machine performance and #PredictiveMaintenance, which not only cuts costs but reduces their environmental impact. @Inteliot via @insightdottech

To be competitive, manufacturers must adopt edge AI and CV for use cases like real-time QC and asset maintenance on the factory floor. Optimizing operations with industrial IoT solutions can improve machine performance and predictive maintenance, which not only cuts costs but reduces their environmental impact—enabling manufacturers to meet their sustainability goals.

For example, working with industrial AI company BirminD, a cement furnace company optimized temperature control—reducing the company’s coal usage by 7%—a figure that equates to 500,000 fewer parts per million of CO2 pollutants in the atmosphere. It achieved these results by installing AI software in the factory machines, an implementation that demonstrates the positive global impact technology can provide.

Another illustration is with global manufacturer Foxconn, which set an aggressive goal to reduce carbon emissions and comply with local environmental regulations. The company worked with Advantech, a manufacturer of edge computing solutions, to manage energy optimization through smart sensors, power meters, and an always-on data collection system throughout one of its facilities. With new visibility into energy use, Foxconn not only developed capacity forecasting plans but also saw immediate improvements in energy efficiency with up to 13% cost savings on average.

Modernizing the Electric Grid Improves Environmental Sustainability

But the problem goes beyond businesses, reaching households across the globe. The impact of climate change and the growing demand for electricity is increasing the challenges for utilities to keep the lights on while also focusing on sustainability, energy efficiency, and decarbonization. Companies that modernize the grid and their delivery of energy services will be at the forefront of revenue generation. But they face multiple obstacles that require electric utilities to rethink how they design, manage, and maintain the power grid.

To start, carbon-neutral energy sources like solar, wind, and battery drive the electricity distribution model to undergo change. We’re moving from top-down, one-way flow of power to a highly distributed network across the other side of the grid. This two-way distributed power requires a level of edge compute that supports making real-time decisions—enabled by AI and machine learning tools.

Building an intelligent edge—starting at the substation where the data lives—and normalizing that data enables greater visibility and insights for faster decision-making. Ultimately, building a data-driven grid allows utilities to maximize the use of renewable energy. The route to achieving this is a software-oriented approach—shifting from hardware- to software-centric, and going from model-based toward data-based, from fixed systems to more agile, scalable, and reliable systems.

Adding more intelligence and more operational capabilities can turn that data into insight, and ultimately to improve the reliability and the resiliency of the grid. 

The Potential of Sustainable Buildings

Beyond changing how the power grid is designed, managed, and maintained, building owners and managers can do their own part to reduce their energy usage.

For instance, the World Economic Forum reports that buildings use 40% of global energy and emit 33% of greenhouse gases. And with more people working from home than ever, some of these buildings are still using as much power even though they could be at half capacity. As such, businesses are transforming their buildings to meet net-zero goals, reduce operating costs, increase efficiencies, and create the optimal environment for a hybrid workforce. Advanced data analytics and AI-powered insights can help achieve these goals.

“Building technology of course has been around for a while, and buildings are already well instrumented. What’s needed is to consolidate all those different workloads onto a common platform, then to look for those insights to drive energy efficiency, lower carbon footprint, and be more energy resilient,” says Michael Bates, Intel Global Sales GM, Energy and Sustainability.

To start, building operators must collect and preprocess data from a diverse set of incompatible systems—from HVAC to lighting, water to air conditioning. Analyzing this data informs how to best optimize the heartbeat of what that building should be, given what it’s capable of doing with the equipment and systems that are in place. When you pull this together, the benefit is that you can start to figure out patterns, and you can build a plan to get there.

Supermarkets are a great example of the smart building payback. Grocery stores are filled with energy-hungry systems such as refrigerators, generators, bakery ovens, and heating systems. One example is Sainsbury—the second-largest supermarket chain in the UK—which has a goal to reach Net Zero by 2040.

Working with Hark Systems, a provider of energy analytics and IoT solutions, the grocer implemented the Hark Platform on 20,000 assets, including lighting and refrigeration. The system retrieves more than 2 million readings per day, detecting anomalies and sending out alerts of potential equipment issues—resulting in energy savings and lower costs. And when energy prices spike in the winter, a preset notification comes into the system from the utility provider, to automatically orchestrate a profile change, reducing the load in the building.

In the future you can see how businesses like Sainsbury’s will be able to become microgrids. Generating its own power and selling it back to the grid means effectively getting carbon-free power. Much of the technology needed for this to happen—solar panels, energy storage units, and platforms like Hark—already exists. This is one path to sustainability where smart buildings can pave the way.

A Vision for Today and the Future

Sustainability is a global imperative, and the adoption of innovative technologies is an essential component to navigating the ascent to a net-zero world. There’s a real opportunity to do something here. It’s not theoretical; it’s not prohibitive; it’s needed. And the appetite is high for IoT solutions that help make it possible.
 

Edited by Christina Cardoza, Associate Editorial Director for insight.tech.