Skip to main content Skip to secondary navigation

Browse Stanford's available technologies by keyword or collection today by exploring our Techfinder Catalog.


Main content start

Credit: Photo by Homa Appliances via

High-Frequency sensor and AI solution to predict and prevent industrial equipment failures.

About the Technology

An image of electrical equipment taken in the B-Dot inventors' lab
Photo credit: the inventors

The B-Dot project is set to transform how industries manage and predict equipment malfunctions, thereby reducing costly disruptions and enhancing safety. Our solution leverages a patented technology that combines B-field sensing with advanced artificial intelligence (AI) models to enable predictive maintenance of electronic systems like motors and batteries. Unlike traditional methods that rely on scheduled maintenance and manual inspections, our approach uses non-invasive sensors to monitor magnetic fields at high frequencies, capturing real-time data that our AI systems analyze to predict potential breakdowns before they occur.

Photo of the B Dot inventors at Stanford University
Photo of the inventors. Credit: Grace Hsieh

Our technology operates much like analyzing the "DNA" of electronic systems, offering insights into their operational health without the need for physical intervention. This high-frequency electromagnetic analysis allows us to detect and anticipate failures, significantly minimizing downtime and extending the lifespan of equipment — even in high-temperature environments. Such proactive maintenance can drastically improve operational efficiency and reduce costs associated with unexpected failures.

A hand holding the B-Dot sensor
Photo of the sensor. Credit: Grace Hsieh

With the inclusion of an MBA intern from the HIT Fund as a key member of our team, we are conducting market analysis and customer research to uncover the most promising commercial opportunities for our technology. Together, we are setting a strong foundation for the launch of a startup focused on delivering a predictive maintenance solution that not only anticipates but also prevents equipment failures — which is especially crucial for industries like manufacturing, energy, and logistics, where downtime is particularly costly. As the global predictive maintenance market is expected to grow exponentially, B-Dot is uniquely positioned to meet this demand with our innovative approach.


Team Members

Debbie Senesky

Debbie Senesky

Associate Professor of Aeronautics and Astronautics, of Electrical Engineering and Senior Fellow at the Precourt Institute for Energy

View Stanford Profile

Anand Lalwani

Anand Vikas Lalwani

Ph.D. student, Electrical Engineering

View Stanford Profile

Joseph Kao

Joseph Kao

HIT Fund MBA Intern, MSX Fellow, Graduate School of Business

View Stanford Profile