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Plug-And-Play Sensors… Are Easier To Use And Are More Secure

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As the Internet of Things (IoT) picks up pace to properly disrupt the market, changes behind the scene affect it in various ways. Let us take a look at what these changes are and the role these play. Colm Prendergast, director of IoT Technology, Analog Devices, speaks with Dilin Anand from EFY


Colm Prendergast

Colm Prendergast, director of IoT Technology, Analog Devices

Q. What is driving efficiency in connected automation systems?
A. Improving efficiency is the prime driver behind connected automation systems. If it is a proactive maintenance system that you are setting up, you need to be able to gain information from the data collected and use that to change the behaviour in the real world. You are using sensors, measurement, data analytics and machine-learning techniques to provide feedback in a preventative maintenance system.

Q. How should one start with setting up a connected automation system?
A. The flow is that you start with the physical process, around which you build your data-collection system. Once you get the system in place, collect data and apply analytics to it. Big Data analytics and machine learning can be done in the cloud, although increasingly there is a trend towards moving analytics to the network edge where smarter devices can be more responsive to the systems being monitored. These systems provide the information needed to implement the behavioural changes for preventive maintenance.

Q. What are the main factors affecting evolution in this space?
A. Top factors affecting this space are low-power technology, advances in sensing and measurement, closed-loop feedback, energy harvesting, energy-independent sensors and low-power signal processing.

Q. How does data analytics work for information collected as videos?
A. Information extraction happens at the node itself in the case of media. Using our BLIP camera system we take video and images at video graphics array resolution, and use that as source data on which occupancy information extraction is done at the node. Once this occupancy information is extracted, only those pieces are sent forth for the next set of analytics. This helps to ensure that the network is not overstressed with data.

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