Event 24
When small production platforms have backup equipment sitting around unused for long periods of time, it often leads to mechanical equipment failures that can cripple production for days or weeks on end. Thankfully, there’s help in the form of new technology. IOT and machine learning can be used to predict mechanical failures with enough lead time to get new equipment on-site before failure to eliminate unnecessary shut-in, and the ability to do this starts at the data layer.
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Join Michele Pelino, Principal Analyst, IoT, at Forrester for a conversation with Calvin Jepson, head of Technical Sales at Particle. Michele will share industry trends and best practices for selecting, deploying, and maintaining an IoT solution at scale, followed by a Q/A session with Cal, in which they'll discuss customer case studies and other insights.
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IoT-Now
To successfully manage thousands and even millions of IoT devices or machines around the world, enterprises need complete autonomy, transparency, self-management and control. They need ubiquitous connectivity, covering multiple countries with different operators.
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IoT hardware is called that for a reason – because it’s hard. Despite best efforts, over 80% of customer IoT projects fail due to an issue at the device level, which is often a connectivity issue in disguise.
In this special pre-Halloween webinar, join Paul Marshall, Co-Founder and Chief Customer Officer at Eseye for an intriguing session to hear some of our customer’s IoT connected device horror stories and how they were able to overcome them.
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