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FogHorn and Honeywell Present Edge Machine Learning for Android Industrial Devices

By Ken Briodagh
April 05, 2019

FogHorn, a developer of Intelligent Edge AI software for industrial and commercial Internet of Things (IoT) solutions, recently announced that Sastry Malladi, CTO, and Ramya Ravichandar, VP of Product Management, along with Scott Bracken, Director, Advanced Technology at Honeywell, will discuss how Honeywell and FogHorn Leverage Android for Smart Industrial Devices at the Google Cloud Next 2019 in San Francisco, CA. The session takes place Apr. 9.

As part of the panel, they will share how their solutions use Android-powered industrial devices with traditional and adaptive machine learning to solve real customer problems. The session will demonstrate emerging use cases, including barcode image reconstruction and device battery lifespan prediction.

The event follows FogHorn’s announcement of Lightning Mobile, the company’s first edge computing solution built specifically for industrial mobile devices. Lightning Mobile is designed to empower operational technology (OT) and field professionals with real-time analytics, machine learning (ML) and AI on mobile, battery-powered devices, without having to rely on connectivity to the cloud, speeding decision making and industrial workflow.

“Properly trained ML models can be deployed on industrial devices to accurately predict asset productivity, failure conditions and significantly enhance machine performance based on the real-time data,” said Sastry Malladi, CTO, FogHorn. “For industrial organizations using Android-powered mobile devices, edge-based machine learning enables massive operational improvements, facilitating real-world IIoT use cases including next-generation barcode scanners and power-efficient monitors and sensors.”




Edited by Ken Briodagh
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