Itron partners with NVIDIA on grid edge integration

Smart energy tech major Itron has integrated its distributed intelligence (DI) platform with the NVIDIA Jetson Platform, a significant strengthening of its grid edge solutions.

Itron, which provides intelligent infrastructure for modern energy and water management, calls the integration an expansion of its AI capabilities at the grid edge. 

The companies recently demonstrated the integration of Itron’s distributed intelligence (DI) platform, including Grid Edge Intelligence applications, with the NVIDIA Jetson platform, representing a significant milestone in their collaboration. 

According to the US-based company in a release, the Jetson platform will allow users to process waveform data from Itron endpoints, using AI for local anomaly detection to identify systemic risks like faults or wildfires. 

Specifically, NVIDIA Jetson’s high-performance compute delivers real-time, low-latency processing of large quantities of data.  When AI is applied to the high-frequency, real-time data collected from Itron’s intelligent endpoints at the edge, detection and classification applications perform inference at the edge and pinpoint faults with greater speed and accuracy. 

These applications also learn—recognising conditions that signal risk—making it easier for infrastructure to predict and prevent incidents that threaten property or life.

AI at the edge

When deployed at the grid edge, says Itron, AI enables faster, more precise fault location compared to traditional methods, while continuous learning reduces threats to people and property. 

This collaboration, they add, combines advanced technology and industry expertise, enabling utilities to extract greater value from complex data sets and address major challenges impacting their infrastructure and consumers.

In their pitch, Itron say that, due to rapidly accelerating grid complexity, utilities must be able to process and analyse high-fidelity data closer to the source to support real-time decision-making. 

This is what their Grid Edge Intelligence portfolio aims to do, supporting distributed intelligence across the distribution grid and enabling utilities to apply AI-assisted analytics at scale. 

Commenting in a release was Don Reeves, Senior Vice President of Outcomes at Itron: 

“As grid topology becomes more complex and threats to resiliency, reliability, safety and affordability increase, utilities require greater visibility into conditions emerging closer to customers. 

“Through our collaboration with NVIDIA, Itron is demonstrating AI at the grid edge, leveraging our DI platform, to help utilities better detect and classify conditions that may indicate faults, wildfire risk or other emerging threats, improving situational awareness and supporting faster, more informed decisions.”

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It is not only Itron that claims that edge AI will be crucial for supporting utilities in maintaining energy system resilience.

Indeed, a blog post by the World Economic Forum (WEF) puts it clearly: edge AI will be a big part of building a smarter, more resilient energy future.

Specifically, edge AI puts intelligence where it's needed most – at the edges of the power networks. Instead of sending all data to a central point, AI tools work locally on or near the grid's sensors and devices. 

This means that real-time insights and faster, automated control help manage the growing number of distributed energy resources – including assets such as rooftop solar panels or EV chargers – and keep the grid stable. 

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In terms of asset maintenance and security, the WEF adds that AI can already predict when equipment might fail, spot faults instantly and balance energy loads efficiently. 

This all comes alongside the booming edge computing market. 

Market research released earlier this year projects the market for edge AI in smart grids to rise from $15.49 billion in 2025 to $19.46 billion in 2026, representing a compound annual growth rate of 25.7%. 

This surge, says the research, can be linked to several factors, including the increasing frequency of grid failures and outages, heightened demand for energy efficiency, the growing integration of renewable energy sources, broader deployment of smart meters, and expanded use of industrial IoT technologies within utility operations.