In the age of smart connected devices – commonly known as the Internet of Things – devices churn out raw data that then needs to be fed into software or analysis solutions to make business decisions.
But now, the channel can infuse the IoT itself with intelligence and mix it with direct human interaction - introducing the concept of creating intelligent things.
The promise of the intelligence has helped drive significant investments in the technology market, with advances in cloud computing, artificial intelligence [AI], and mobility all lending itself to this phenomenon.
In the year ahead, a shift from standalone intelligent things to a collaborative intelligent things model is coming.
According to Gartner, the overall IoT opportunity for IT service providers is “immense”, with total services spending for the IoT sector hitting $US235 billion in 2016, up 22 per cent from 2015.
“At first glance, those IoT opportunities involve steep learning curves in complex areas such as network sensors, big data, mobile privacy, security, analytics and more,” Channel Dynamics director, Moheb Moses, said.
“But take a closer look and businesses will discover a path from familiar technologies, including databases, networking and endpoint management, that lead towards the IoT market.”
In building on the vision of bringing intelligence to everything, everywhere and for everyone, Rivium CEO, Robert Silver, believes intelligent things offers businesses the ability to make decisions for the future based on data collected.
As a Splunk partner focused mainly on machine data analytics, the Melbourne-based company is seeing that as technology moves forward, more capabilities are being embedded into it around predictive-based analytics and AI.
“Predictive-based analytics, in the technologies we sell and implement, bases predictions on prior behavior with the data itself,” Silver added.
“We can ingest a year’s worth of data from different environments, then start to predict what sort of things are going to happen in the future with that data. An example is our work with a utility company that generates electricity.
"The customer had a number of diesel generators explode, so through analysing that data, we understood the environment and predicted whether it was going to happen again.”
Another project Rivium was involved in with Splunk was monitoring bus networks for early, late and on-time arrivals, before correlating that against other data, such as road works data, to determine why buses were running late on routes.
According to Silver, the uptake has been high within the security monitoring space in Australia, with government, financial services and online the most popular adopters of intelligent things components.
“With these predictive solutions, we can start to do things like anomaly detection and behavior that is not considered normal based on what we’ve seen in the past,” he added.
In terms of customer uptake, Silver said conversations with customers around this topic have been seamless, especially when it comes to security, as it makes it easy for them to understand.
“If we start to apply it to other verticals like transportation and logistics, which we’re newly entering into, we can still have a security conversation with organisations like that, but predictive analytics and intelligent things can be used a lot more effectively around movement data and traffic monitoring.”
Silver said customers now want to be more educated around intelligent things and predictive analytics because they are not familiar with what can replace legacy technologies.
