At its highest level, the Internet of Things is frequently mentioned in the same breath as the increasing number of connected sensors.
But as the IoT continues evolve, so too does our understanding of what it will look like and how it will function.
As the number of sensors increases, so does the amount of information they gather. And all that data is booked for travel to the cloud, leaving the IoT awash in information and overburdened to translate it into insight.
There are other considerations, for instance, what about the power needed to transfer all this data? What if you’re putting garbage into the cloud – how can you expect to get insight from it? What if you need immediate action due to an out-of-bounds measurement or algorithm? What if you simply have to keep data local? What if the network fails?
Internet of Things (IoT) is Much More Than Connected Sensors
This growing complexity is changing the thinking in many IoT circles. Key analysts such as McKinney suggest that as little of 1% of cloud data is actually used. Even massive cloud partners like Microsoft are switching their focus from the cloud in the center to the sensors at the edge. And the edge can often be an environment of extremes.
Consider a sensor in the heart of the desert, and another deep in the arctic. Or sensors on a moving robot in a factory full of radio interference. Just surviving and operating in those extreme settings is challenging. But what if the data being gathered is a complex waveform, or so large that it will take significant power to send it regularly to the cloud?
Extreme IoT applications typically require a systems level approach to designing the end-to-end application. Precise sensing and measurement under the harshest conditions, low power signal processing at the node, and reliable connectivity are three key pieces to getting the most from the Extreme IoT.
One of the phenomena of extreme IoT is that things just simply won’t stay still!
The Internet of Moving Things
High performance industrial sensors are enabling a shift from traditional mechanical, fixed-function, stationary devices to increasingly intelligent, autonomous, and mobile machines. Accurate motion tracking and location determination of the sensor node are becoming central to application success. Location information from the node will enable applications such as smart farms leveraging autonomous land and air vehicles to reduce costs and improve yields. While in hospital operating rooms, it will help precision-guided robotic arms provide the surgical precision needed to produce successful outcomes. In both scenarios, correction for outages or inaccuracies in the primary sensing/feedback loops that enable guidance and controls is critical for protecting machinery and lives.
From Rant to Reality:
A solution can be found in high-performance MEMs IMUs specifically engineered for extreme IoT applications, such as the ADIS1647x and ADIS1646x from Analog Devices (ADI). They are capable of supporting sub-degree pointing accuracy and precise geolocation, while also providing the necessary size and cost efficiencies. They reduce angular jitter, and provide primary guidance during outages or disruptions of other sensors to determine the system-state within complex applications. They advance what was once simple machine measurement into machine control, and further again towards true machine intelligence.
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