At Discover London 2015, Hewlett Packard Enterprise announced Internet of Things (IoT) systems and connectivity solutions that enable customers to more efficiently collect, process and analyze IoT data. Here, we share our vision for IoT.
IoT is one of the most important technological innovations of the past decade. Analytical insights from IoT can lead to valuable business outcomes like automation, improved productivity, reduced downtime and enhanced knowledge of what’s going on at your company. McKinsey estimates that IoT will have a total potential economic impact of $3.9 trillion to $11.1 trillion a year by 2025.
IoT is, well, exactly what it sounds like: A network of physical things that are connected to the Internet. There are three key elements of IoT:
- Devices – Rather than just smartphones and servers, IoT “devices” can include everything from household items like thermostats and trash cans to industrial systems such as wind turbines and medical equipment.
- Data – The real value in IoT is harnessing the data from these connected devices and using the insights for better decision-making.
- Connectivity – IoT requires a reliable network connection that allows data to travel seamlessly from point A (where it is collected) to point B (where it is processed and analyzed).
Computing at the Core Vs. Computing at the Edge
One way to approach IoT is to capture data from connected devices and send it back to the “core” of your system—typically a data center—for analysis. Huge volumes of data are collected and analyzed over time so that you can make long-term changes to improve performance and efficiency.
A more recent approach—one that is central to Hewlett Packard Enterprise’s IoT strategy—is computing at the “edge,” or closer to the source of the data. This major IoT shift is happening as organizations are looking to move computing power, data acquisition and data management to the edge of the network, outside of the traditional data center.
Increasing capabilities at the edge of an organization’s network allows faster access to relevant data and requires less bandwidth to transport irrelevant data. Rather than logging and transporting all the data collected in an IoT network and sending it to the core for analysis, data can be more efficiently and quickly sorted so that few critical data points can either be analyzed at the edge or sent back to the core. Computing at the edge makes immediate change possible—change that comes in response to a piece of data from the real-time activities of your business.
How It All Comes Together
Let’s take an example.
If a hospital is running a connected IoT infrastructure that computes at both the core and the edge, it’s primed to make the most out of its machines, staff and patient well-being. Through long-term analysis and computing at the core, hospital officials are able to make adjustments to delegate machine use and make staffing decisions to better accommodate higher-traffic times or departments. This is an important process, no doubt, but it requires a lot of bandwidth, time and energy to send all the data to the core, analyze the relevant information and receive actionable insights.
With intelligence at the edge, data from new patient monitors can tell you whether patients are awake or asleep as well as provide real-time information about the breathing rate, skin temperature, body position and activity level—with alerts about any abnormal conditions delivered directly to the physician’s device. This edge computing model distributes the workload rather than sending it all to the core, allowing faster access to relevant data, which enables physicians to prioritize certain patients during their rounds or respond to immediate concerns as they emerge.
At the end of the day, moving more computing power to the edge results in an organization that’s run more efficiently and effectively than was even remotely possible a decade ago.