IoT becomes the gateway to edge computing.

IoTbecomesthegatewaytoedgecomputing.

Recently, there has been a lot of discussion about IoT platforms. Analysts have even created a category for developing IoT platforms.

While there are many IoT products on the market, most do not have any embedded IoT platforms that can solve a range of different business problems.

In fact, it's probably best if the IoT is not seen as a platform, because the IoT is not a platform - edge computing. Fundamentally, the IoT is not a platform for the consumer space. Devices such as light bulbs, sensors and cameras talk directly to solutions on remote cloud services, often with some hub acting as an intermediary. Edge computing used to be wireless module, and usually is, vendor specific. In any case, it is usually a very simple architecture.

The Case for Boundary Computing

The Industrial Internet of Things is always going to get more and more complex. Most architectures contain at least one gateway close to sensors and actuators. In this model, latency-sensitive events can be filtered, aggregated, and responded to in real time. In fact, most industrial IoT architectures are still complex, with multiple layers of gateways and other compute, storage, and network resources.

What has happened in the last few years is that many different industries have adopted edge computing, especially for loads that do not appear to be similar to the industrial IoT. This hybrid computing represents a reversal of the common perception that everything will inevitably move to the public cloud.

Edge computing can be seen as the latest enterprise IT footprint. In a sense, it is a recognition that enterprise IT is heterogeneous and cannot be solved in one way. Edge computing can also be seen as a new platform for multiple workloads.

Where is the Internet of Things going?

There are two main paths to edge computing-based IoT. First, IoT is a workload that uses edge computing as a platform.

However, not all edge computing applications are IoT, although many contain at least some IoT elements. For example, computing in the distributed retail sector is a form of edge computing. In this context, IoT might be the use of scanners, Bluetooth or RFID.

However, in this case, the edge computing platform may not be the main issue. Nevertheless, technologies similar to those mentioned above are becoming more common, so more and more workloads are likely to contain at least an IoT element.

Other edge workloads are more straightforward for IoT applications. For example, chemical plants, refineries and similar facilities are increasingly using drones and computer vision to quickly identify problems and perform predictive analytics. The amount of data that needs to be processed can be huge. Sometimes it's best to keep everything for future needs. However, by inspection, all the data corresponding to the nominal operation may not be needed.

At the same time, the IoT can be seen as an entry point into the edge. Ultimately, edge architecture exists for a reason. It is usually to gain information about the state of the physical world so that the enterprise can take action. If the robotic inspection mentioned above, the operation might be to dispatch a maintenance team. For the last retail example, it might be the resupply of goods that arrive at their reorder point.

This data can also directly trigger a physical response. One of the reasons companies are decentralizing compute and storage to the edge is to be able to respond to events in real time. By using local processing of transactions, companies can avoid the latency and network reliability issues associated with sending alerts to a central server and waiting for a response. In terms of trends, the IoT will become increasingly important in terms of data access.

Related article reading:

Three IoT applications can be a game changer in sports.

What is the Internet of Things? How do you use it and what impact will it have?

What is the Internet of Things? Three minutes to the Internet of Things!

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