7 Questions About the Internet of Things

- Technology - Jan 09, 2015

Analyst firm Gartner predicts that there will be $300 billion spent on Internet of Things (IoT) products and services worldwide by 2020.

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But why should businesses spend their money on IoT projects in the future and what opportunities will there be for them from this investment?

We spoke to Patrick McFadin, Chief Evangelist for Apache Cassandra at DataStax, to find out what benefits businesses can expect from the Internet of Things. Here’s what he had to say:

BRE: What is the Internet of Things?

PM: The “Internet of Things” is a technical phrase that has been around for many years – it describes how everyday devices can connect to the Internet and create real-time data on what they are doing.

READ MORE: [Infographic] What the Internet of Things will Look Like in 2020

While it’s been possible to connect things like refrigerators and washing machines to the Internet for a few years, it has remained a niche market...until now. This is changing the way companies think about how to use data from connected devices.

Why is this data becoming a vital asset?

The value of collecting data comes over time. As you collect more and more information, you start to get a very accurate picture of preferences, location details and how your business you can profit from it. People do this every day and call it “experience”, but it applies to potential projects around the Internet of Things, too.

Saving data from devices across a network creates an asset called time-series data, listing what took place and when. Once you start collecting this information, you can quickly begin to look at where and how it can be used to make intelligent business decisions.

You say data allows you to make smarter and more strategic decisions. Can you give me an example of this for Internet of Things today?

Sure. i2O Water is a UK company that stores data about what is happening on water networks. For the utility companies that i2O Water works with, this information can be used to alert them on where maintenance might be needed, as well as where money can be saved through reducing pressure levels.

This use of data over time allows utility businesses to take immediate action and save money on repairs where they can, as ongoing maintenance is far more cost effective than fixing damages. More generally, companies can think about getting data from customer assets over time to improve the service they offer.

How does data help you understand your customers … and yourself?

Creating time-series data is useful, but it is not valuable unless you know how to use it. Analytics can help here. While many companies have lots of data stored, not all of them know how to use it to their advantage. Simply taking data from connected devices is not magically going to help you cut costs or think up a new service; you’ll need to use that data in the right ways.

Buildings are another great example. Heating, lighting, air conditioning and more general electricity use all add up in different ways. However, looking at each of these in isolation won’t add up to much in the way of savings. Instead, combining data from each can help spot where more power is being used, which can be particularly useful for companies with multiple locations.

What does this look like in practice?

Combining data from multiple sources is where there are opportunities for the future. For example, U.S. retail chain Walgreens sourced data on power use across its 8,000 stores, storing data from each of these building systems and analysing the data created on power consumption at each location.

Additionally, a large store location in Texas will have different power requirements than a small office in Seattle. Offices in different regions or countries will have different power needs. However, the ability to look at “like for like” situations can really help cut costs.

By analysing what those individual locations consumed, the facilities management team could get a picture of best practices and encourage these at other sites. Walgreens was able to reduce its spend on power by approximately $19 million a year.

How does spotting different patterns and how things are changing over time lead to more value for the business?

Everyone, by now, has heard the example of analytics spotting that the sale of diapers, or more commonly known as nappies in Europe, increased in correlation with beer sales on Fridays. This was apparently caused by fathers going out and doing the shopping on their way back from work. The result from this for retailers was to place those items closer to each other, increasing sales of both.

While we aren’t there yet, the Internet of Things will have this moment as well. It may come from car technology, where spotting information on driving styles and use patterns could be correlated against wider traffic conditions. Imagine if you could spot where different drivers’ behaviour could have an impact on service plans and safety recommendations, even on the same vehicle?

The opportunity here is to use this information in a way that benefits the individual driver and makes their life better, while also providing greater sales to the company involved. At the moment, the data that companies source around driving is tied to the phone or the vehicle, rather than the individual.

What happens to all this data once it has been created?

The value from data is only possible when it can be analysed. The devices that are being connected up to the Internet are not “smart” themselves. This means keeping a lot of data over time, which requires management.

For business projects, it’s likely that data will have to be stored. There are two reasons for this – one is that it’s possible to spot more opportunities when you can see what is taking place over time. The second is that companies may have their own compliance requirements to consider around that data once it is created.

There are plenty of options available, whether you store the data yourself or use a cloud provider to host this information. Whatever your approach, it will have to keep pace with the creation of the data by the devices themselves. This comes down to how much data is being created, and how fast it has to be written to the database.

There are elements like security, data protection and compliance that have to be considered too. Customers will want to know what their data is being used for, who has access to it and how it benefits them. For companies, the emphasis has to be on how it helps reduce costs to them, or provide better quality of service.

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Comments(3)

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LumenCache    Jan 11, 2015
Adding time series data will also allow automatic device pairing. With billions of devices planned, they will need yo self assemble to some degree
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   Jan 10, 2015
Hello Fiona, thanks very much for your input and glad you found the Q&A helpful.
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Fiona McNeill    Jan 09, 2015
Thank you. This is a helpful article, addressing some of common questions organizations are asking about IoT. You mention that: “The value of collecting data comes over time”, and I’d just like to emphasize that it’s the time element that is the single commonality that underpins the IoT – with different types, formats, communication protocols and more associated with each individual ‘thing’. And that it’s possible to collect windows of data (over a pre-defined time period) within the data streams generated by connected things, in addition to collection of time-stamped data for more in-depth analysis out of stream. Your readers may be interested in learning more about how analytics works in the IoT, which can be found here: http://www.sas.com/en_us/insights/big-data/internet-of-things.html. As you indicate, combining data from multiple sources is where there are opportunities for the future. In addition to connecting data from different sites, as with your Walgreens example, different types of data can also be collected from things – from social media unstructured data streams, sensors and devices – analyzed together and continuously assessed for complex patterns. As you state: “The value from data is only possible when it can be analysed.” And to take devices from being smart to being brilliant, analysis will go beyond monitoring current conditions to advanced analytic predictions of ‘things’ - helping organizations, people and the things themselves - prioritize the next best action.