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IoT and the Case for Intelligence at the Edge
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IoT and the Case for Intelligence at the Edge 

There’s good reason to believe the hype. Sensor data pent up in the Internet of Things (IoT) can be unleashed to make homes, cars, businesses, utilities, and even cities smarter.

“IDC estimates that IoT enabled hardware will grow at over 20 per cent year over year through 2020, resulting in over 30.3 billion connected devices. While many of our early deployments are in population centres, where ubiquitous high speed wired and wireless connectivity is common, some of the most valuable IoT assets will be the exact opposite – acting as our proxies in places where people, and therefore networks, don’t reside,” says Dave Pearson, IDC Canada’s Research Manager for Enterprise Storage and Networking.

Our challenge is to develop systems that capture and process data fast, efficiently, and at the point where it can have maximum impact.

The Case for Adding Intelligence at the Edge

Many of today’s sensor networks have fast access to clouds, given that much of the IoT, especially Consumer IoT, has formed in areas where it is convenient to deploy. But as it grows, we should expect companies to bring sensors and data acquisition systems to things in remote areas, resulting in use cases that the cloud would be ill-suited to support.

Today, many organizations are focused on the concept of “sensor to cloud.” There’s good reason for this, as the cloud has proven to be a fine progression from traditional data centre IT. So, why not impute the benefits of the cloud on the processing of sensor data from the IoT? Many organizations are adopting this stance, but there are seven key problems with this approach.

  1. Latency is too important. Smart cars need to process information instantly to allow them to detect obstacles on the road ahead. The cloud can’t provide that, and shouldn’t be expected to.
  2. Bandwidth is too sparse. Rural areas are generally connected via expensive satellite systems that don’t have much bandwidth to begin with. Sending information to the cloud this way can take far too long, or make it impossible to yield useful results.
  3. Compliance requirements would complicate data sharing. Governments and corporations have put restrictions on how far data can travel. Thus, collecting data in London and shipping it to Paris for analysis isn’t an option anymore.
  4. Transmitting data would create security problems. Attackers target data that is in motion because it’s usually tougher to secure information that’s in transit. What’s more, data that’s being sent for analysis is also usually worth encrypting, which can make files fatter and transmission materially slower.
  5. Pushing data to the cloud costs. Bandwidth isn’t free and sometimes it isn’t cheap.
  6. Cloud access duplicates data collection efforts. There will be some duplication of software and hardware if both the edge and the cloud are equipped for massive IoT data.
  7. Distance creates data corruption that pollutes analysis. Have you ever participated in a cross-border phone call? Between the static and the dropped words, you get a sense of what you’re hearing on the other end but the connection is still unclear. Too much data is being lost during transit. Cloud connections can suffer from this same problem.

In sum, we can’t assume that pervasive connectivity will always allow the proper sharing, combining, and processing of data. Pervasive connectivity may not be available or suitable on an oil platform floating in the Gulf of Mexico, a secure manufacturing floor, or in the wide-open fields of an Iowa farm. In addition, it will not be performant enough for the astoundingly massive data to come from future autonomous vehicles.

Therefore, instead of having to transmit data to faraway servers, in many cases it’s more practical to install portable, rugged, data centre-grade computing systems onsite. Processing data at the time and place it’s collected means information becomes insight faster, leading to intelligent action that can save resources or even lives.

Future of the IoT: From Edge-to-Cloud

IDC predicts that as much as 45 percent of IoT-created data will be stored, processed, analyzed, and acted upon near or at the network edge by 2019.

“The ability for IoT devices to create data from a variety of sensors and inputs with little or no human interaction is an entirely new development in computing. The expected demands of IoT-generated data will exceed all other forms of big data, and eventually all types of human generated content and data,” Pearson says.

“Computing capacity, and more importantly network capacity, cannot keep pace with the exponential growth in new information, leading vendors to develop new and more powerful ways to deal with the glut of data at the edge.”

Enterprise organizations seeking to seize opportunities created by the IoT will have to employ intelligence at many stages of the end-to-end IoT solution – from the thing, to the edge, to the data centre and cloud, and many areas in between.

Charlie Atkinson Charlie Atkinson is the Managing Director and Vice President of the Enterprise Group at Hewlett Packard Enterprise Canada. You can follow Charlie on Twitter:  @CharlieMeansBiz.

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