Energy infrastructure is responsible for powering multiple facets of our daily lives. From transmission lines to transformers, the health of these systems directly affects everything from heating our homes to powering our public transit. In a country as vast and climate-diverse as Canada, maintaining that infrastructure has always been a challenge. But now, predictive maintenance is offering a smarter way forward.
Predictive maintenance uses sensors, AI, and real-time data analytics to detect equipment issues before they cause failures. Rather than waiting for something to break or sticking to fixed maintenance schedules, energy providers can now anticipate problems, address them early, and avoid costly outages. This could mean that energy providers could be proactive in operations rather than hindered by crisis management.
This shift is already underway across Canada. In Ontario, utilities are using thermal imaging and machine learning to identify overheating components in substations. BC Hydro is deploying vibration sensors on transformers to detect early signs of wear. In provinces like Manitoba and Alberta, where freeze-thaw cycles can wreak havoc on power lines, predictive tools are helping crews pinpoint stress points before winter hits.
Fewer emergency repairs mean lower operational costs and reduced carbon emissions from maintenance fleets. For remote and Indigenous communities, predictive tools can help limit disruptive outages and support energy independence by keeping local systems running smoothly.
Startups and Canadian researchers are playing a key role too. Companies like Copperleaf and AssetWatch are developing AI-driven asset management platforms tailored to utilities’ unique needs. Meanwhile, government grants are supporting pilot projects that bring these innovations to rural and underserved regions. Of course, modernization comes with its own learning curve—utilities need skilled staff, strong cybersecurity, and capital to implement these systems. But with aging infrastructure and growing demand, the timing couldn’t be better.
