Human judgment will remain essential to making the most of data-driven technologies. While AI can take care of the heavy lifting, people will decide what data and insights to prioritize so the systems deliver smarter, more sustainable results for all stakeholders.
Governments and utilities have spent the past few years building smart facilities, where sensors and cameras monitor infrastructure health and support early maintenance. Unlocking the full potential of these smart devices can enable sectoral leaders to meet critical challenges around reliability, costs and sustainability in the face of rapid urbanization, disruptive weather events and aging assets.
Think of these investments as the paved layers of a highway under construction. Such an artery connects towns within an area, but without detailed lane markings and adequate signposts, navigation becomes a challenge.
Similarly, a wealth of data is now streaming in from investments in internet of things (IoT) devices, including radar and 5G-equipped appliances. However, this data remains an underutilized resource. As we look to the first round of sustainability targets in 2030, the next wave of digital transformation leading to Industry 5.0 promises to turn this data into a strategic asset for infrastructure operators and city managers alike.
The rapid digitalization of infrastructure is already shaping how we live, work, and sustain our environment. With five years to our first net-zero deadline, utilities can further leverage advanced technologies to build robust, efficient and decarbonized systems, says Gary Wong, Global Segment Leader of Power, Utilities, and Infrastructure at AVEVA
Just like adding traffic lights and signposts to the highway above, the answer is in collating, contextualizing and infusing this data with artificial intelligence (AI) analytics, and then sharing it with internal and external partners on premises or in the cloud. In the process, industrial workers across the value chain gain the insights needed to make better decisions and improve efficiency and sustainability. IoT deployments become high-performing systems.
Connecting ecosystems for decision-making insights
Sweden’s Roslagsvatten understands the benefits of a connected ecosystem that brings together around a central stream of self-serve analytics. The water and wastewater manager has expanded to serve 200,000 customers in several municipalities, operating 25 treatment plants and 270 pumping stations. With incremental growth came a diverse set of legacy systems, leading to information bottlenecks across the network.
Inspired by developments in other industries, Roslagsvatten responded with a multi-step approach: it digitized brownfield assets, added new projects where necessary, and standardized operational technologies on a secure, open-standard platform. Data feeds from all the assets were centralized and contextualized within a single-window view. Armed with comprehensive real-time industrial intelligence, operators and engineers can now make quick decisions together, troubleshoot faster, save energy and resources, and scale their business easily.
Alongside, Roslagsvatten has enhanced its asset management and boosted end-to-end efficiency. Upgrades are faster with this future-ready system, with handover costs down 40%.
Collaborating for mutual benefit
Connected industrial ecosystems boost cooperation within a company, but also foster radical collaboration externally across the value chain. With industrial intelligence as a service, ecosystem partners (and customers) unlock 10% higher profitability, 3x return on investment and up to 20% higher sustainability performance, data shows.
Closer collaboration will be essential as infrastructure prioritizes net-zero targets and lower emissions, spurred on by policies such as the US Federal Sustainability Plan.
Increasingly, utilities are also partnering with their biggest customers to understand consumption needs. Power companies now work with water utilities or industrial customers to rationalize outcomes on both sides. Teams at California Water Service (CWS), for example, unlocked significant savings with insights from cloud-based AI analytics. They can now forecast peak energy usage better and base future plans on solid data. Real-time coordination also benefits CWS’ power supplier: there is less peak-time strain on the grid.
Solving for net-zero emissions
Infrastructure players on the road to net-zero are also shifting to renewable sources of energy while working to get more from ageing assets. With better insights into intermittency around sources such as wind and solar, schedulers can predict peak demand periods and customers can shift consumption to quieter periods. At the same time, optimizing legacy assets can help utilities serve a growing customer base without major capital investments.
San Francisco-based cleantech start-up DERNetSoft works with a number of prosumers (active energy users who both produce and consume energy from renewable sources). Among these is a healthcare customer that implemented a cloud-based, scalable IoT platform to bring together energy data from 1,200 buildings. AI insights uncovered numerous inefficiencies, saving millions of dollars in cost reductions and reimbursements for overproduction.
Optimizing for agility and resilience
Interconnected systems enable utility engineers to optimize existing infrastructure and prevent service disruptions from security issues or climate events. This approach improves asset longevity and operational efficiency, reducing the need for costly replacements.
The Adani Group, India’s largest private power producer, has improved operational efficiency and reliability at eight thermal power plants across the country. Success lay in deploying a cloud data management platform to streamline data collection, access, analysis, and reporting.
Legacy tools across the network have been united into a single-window interface and teams now have access to decision dashboards that enable them to anticipate and mitigate risks, reducing costs and carbon dioxide emissions.
Doing more with less, thanks to deeper insights
Upgrading to advanced digital technologies, like any change management process, comes its fair share of hurdles. Data silos, regulatory complexity and legacy systems can all slow down progress. However, with the rapid growth of AI and cloud adoption, even infrastructure workers on limited budgets and can make the most of existing assets and optimize their value chains.
The overwhelming majority (95%) of infrastructure operators say industrial AI solutions are essential to staying competitive in today’s challenging business landscape[1]. More than two-thirds (69%) will respond by investing in digital industrial intelligence solutions within 12 months, so their teams have the tools they need to do their jobs better.
Human judgment will remain essential to making the most of data-driven technologies. While AI can take care of the heavy lifting, people will decide what data and insights to prioritize so the systems deliver smarter, more sustainable results for all stakeholders.
Infrastructure players have made strides by deploying IoT and other smart devices, but the true leap forward lies in harnessing advanced technologies like AI and cloud computing. The deeper operational insights they provide give industrial operators the tools to address challenges such as rapid urbanization and climate, and to future-proof critical systems for tomorrow’s demands.
