IoT Data Visualization

Andy Slote - Director of Customer Success for ObjectSpectrum

May 1, 2020

On top of all of the Internet of Things application functions operating on the “server-side,” there is the all-important visual aspect of an implementation. For turning much of your IoT data into useful, actionable insights, the optimal toolset for creating the data visualization is one that strikes a balance between ease of use and a strong ability to create the best optics.

There are many tools and platforms for IoT data visualization, offering the promise of “no-code,” purportedly to enable faster solutions. Some even allow you to create your charts, gauges, etc., with drag-and-drop capabilities. While it’s no longer necessary to build everything from scratch, look closely at these products to see if they give you the flexibility you need to develop the optimal user interface.    

An alternative to drag-and-drop capabilities are environments employing a “declarative” method of creating visuals. A declarative system essentially “asks” the user to describe what they want. The system then uses that description to deliver the desired result. For example, if you need a chart, simply declare the attributes of that chart, rather than writing instructions or code to create it. These tools often strike the best balance between speed and flexibility.

The world is increasingly going mobile, and those who are doing IoT visualization design need to keep that in mind. In addition to designing for desktops, putting the data into a readable format for tablets and mobile phones should be relatively easy to do with the platform you choose. 

For all of your displays, data should be appearing in real-time, without refreshing the screen. Using an application layer protocol like Websockets supports real-time data transfer to avoid the need for refreshing.

Once you know there are many types of visuals available, how robust are the options for titles, labels, legends, etc.? Can you choose your fonts, sizes, and colors?

Charts are one of the universal representations of IoT data. Look for a platform that lets you create just about every type of chart. Basic line, bar, and column charts may be adequate initially, but the best visual may require a less common type like a scatter or area chart. How about stacked representations or 3-dimensional ones? Pie charts with more than one data series? A “thermometer” gauge?

One of the prevalent “use classes” for IoT is asset tracking. Attaching a device to an asset to monitor its position may be a weak solution without the benefit of outstanding visuals. Is the asset outdoors? Showing the position and movement on topographic or road maps is usually an absolute requirement. For indoor asset tracking, tracking the location on a schematic of a room or a floor plan is a great representation. For the symbols representing the assets, how about the ability to place something of resemblance, like an image of a truck, sprinkler, or construction vehicle for quick identification.

Have you heard of a Tooltip? Also called a Live Tooltip, Infotip, Live Legend, Mouseover, or Hoverbox, it’s the window that pops up when your cursor hovers over an object on the screen. These are great for getting a little more information about the item on demand. Make sure this highly useful feature is available with flexible configuration.  

You will probably opt for some kind of standard view of your data on charts, a format for alerts, default date ranges, etc., but you can benefit more when these views are interactive. For a chart, you should be able to change the date range easily, for example. Clicking on legends to drag the date range to lengthen or shorten means doing it with ease, versus keying in dates or selecting one from the typical “popup calendar.” When an alert sets, the information is often general (it may even be as simple as a color like yellow or red). It should be your choice to drill down by clicking directly on the alert. Drilling down is especially useful on mobile displays where the priority is to warn, with a need to look at the underlying data often being optional.

As you learn how your information shows best, you don’t ever want to be stuck with a tool that limits your options.