In a contributed article for Internet of Business, Emil Eifrem, CEO and co-founder of graph database company Neo Technology, presents his vision of how to create interconnected, smart physical environments.
Smart homes offer the promise of fine-grained, real-time operational control, and their impact on our common urban environments is already being felt in multiple areas, from waste and power management to entertainment to public safety.
Consumer interest and acceptance of the technology is rising, with 52 percent of all respondents to a recent US survey planning to buy a smart device in the next two years. Of those who already own smart devices, 84 percent said they may make another smart purchase in the next two years.
Three-quarters of German internet users, meanwhile, say they would consider purchasing smart-home technology.
However, there is still a long way to go to deliver smart environments beyond these isolated pockets. A smart home will need sensors, networks, devices, cameras, power grids and smart water and power meters to reach its true potential, for example. And they will only really be effective if these are all linked up – meshed together as a connected Internet (network) of many things (devices) – by a third party.
In other words, an IoT structure will have to underpin any smart home projects. When a new item of equipment or sensor comes online, it will want automatically to seek local controllers or other devices that it needs to listen to or share data with, while the powering up or down of just one individual sensor may create or end dozens of connections – maybe even hundreds.
Connections and complexity
The question then becomes how do we manage this density of connections and complexity if we are serious about going smart on a metropolitan scale?
We need to go back to that network to see the answer. Most IoT-based applications deliver by making one or more data sets link to one another. However useful connections like this are more than lines between entities; they need to include useful information, such as direction, type, quality, weight, and more.
While it’s true that simple smart home IoT problems could be handled by a relational database, they’re not an especially satisfactory fit, as they represent data as tables, not networks, and queries strain a data structure not designed to map connections.
That’s why increasingly observers think that level of device IoT functionality can only be implemented in a new form of database as an integral part of each prospective smart home network.
Graph databases could be the ideal option here, as they process complex, multidimensional networks of connections at speed.
A case in is telco Telia Company and its new graph-based smart buildings initiative. The company has created a new digital ecosystem and platform for broadband connections called Telia Zone, which has 1 million plus homes signed up and is currently being rolled out to a further 930,000 households – with smart home management a major feature of the service.
With Telia Zone, the home owner can detect when people are entering or leaving the house, setting triggers and rules for adjusting heating, lighting – even appropriate musical accompaniment, like your favourite musical track greeting you on entry, among many other services.
It’s a genuinely innovative smart home service. And it’s all based on graphs. According to the team behind Telia Zone, most of the APIs needed are relationships between different types of events or different types of data, and graph databases are the best way to connect up nodes.
Graphs can easily model these relationships, plus they are also highly flexible; Telia Company does not know exactly which APIs it will go on to develop, but graphs can create new connections on the fly and make new APIs out of any that may become desirable. In addition, Telia Company wants to explore AI (artificial intelligence) and Machine Learning, and graph is also the best way to handle that.
Data at scale
Given the overwhelming amount of data and connections that accumulate over even the shortest period of time in any IoT-powered smart building scenario, traditional databases will struggle to get any coherent, overarching view on what’s going on. In the Telia Zone case, the database is expected to have 13 million devices as individual nodes, with 20,000 to 30,000 events per second.
That’s the kind of scale that the smart home owner will demand – suggesting that it’s graph-based IoT management that will turn out to be the shortest way to get us to the smart home future we all want.