How Computer Vision Ensures Grid Reliability | Noteworthy AI's Chris Ricciuti | Internet of Things Podcast

In this episode of the IoT For All Podcast, Chris Ricciuti, Founder and CEO of Noteworthy AI, joins Ryan Chacon to discuss how computer vision and AIoT are helping utilities ensure grid reliability, resiliency, and safety. The conversation covers the evolution of computer vision, the challenges faced by utilities, such as aging infrastructure, extreme weather events, and increased demand from electric vehicles and data centers, real-world examples of how computer vision improves grid management, and advice for organizations on adopting AIoT.

Chris Ricciuti is a seasoned technology entrepreneur and executive with over 20 years of experience at the intersection of software solutions and industry applications. As the Founder & CEO of Noteworthy AI, Chris leads a groundbreaking company that helps electric utilities enhance the reliability, resiliency, and safety of the electric grid using fleet vehicle-mounted cameras, edge computing, and computer vision.

Noteworthy AI provides fleet vehicle-mounted smart cameras and AI that help utilities improve the reliability, resiliency, and safety of the electric distribution grid at scale while reducing O&M costs. By operating autonomously during routine vehicle operations, their technology can increase situational awareness and realize cost savings and efficiencies across various use cases, including geolocation and asset inventory, asset inspection, vegetation management, joint use/attachment compliance, and lighting audits.

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More about Noteworthy AI: https://www.noteworthy.ai/

Connect with Chris: https://www.linkedin.com/in/ricciuti/

(00:00) Intro

(00:16) Chris Ricciuti and Noteworthy AI

(01:20) Evolution of computer vision

(04:25) Challenges utility companies face

(09:05) Training computer vision models

(11:28) Real examples of computer vision

(14:07) Accelerating extreme weather response times

(17:46) Why utility companies need to adopt AIoT

(19:11) Future of computer vision and AIoT

(20:11) Advice for adopting computer vision and AIoT

(21:30) Learn more and follow up

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