Over the past few years, the Internet of Things (IoT) has moved from hype to reality. From monitoring pollution levels to the creation of smart carparks, IoT applications have solved numerous issues everywhere. Businesses have also started to realise the potential of IoT technology to help streamline operations, collect data and understand their customers better.
As companies accelerate their embrace of the IoT, the web of connected devices will only continue to grow exponentially. In 2018, there was a total of seven billion IoT devices in use. An industry report noted that by 2022, over 29 billion devices will be connected, with around 18 billion of them related to IoT.
While the first wave of IoT brought connected sensors that digitalised the physical world and enabled the automation of mundane tasks, a key problem was that many existing solutions did not work well together, explained Mr Tan Kar Han, Head of Product R&D, NCS.
Better AI creates better IoT, and vice versa
Market research firm Gartner predicts that by 2022, more than 80 percent of enterprise IoT projects will include an artificial intelligence (AI) component, up from only 10 percent in 2018. Designed to allow onboarding of a large variety of IoT devices, these platforms deploy AI to consolidate and analyse the data collected, thereby helping to unlock the full potential of new and existing IoT solutions.
An example of AI-IoT convergence is that of modern ‘smart’ buildings deploying both technologies for advanced climate control. Conventional systems currently in use are reactive: simple thermostats would sense temperature fluctuations and proceed to switch the air conditioning on or off.
“However, there will be a slight delay with thermostats due to reaction time. For example, building cooling systems can be slow to react to sudden changes in conditions. If there is a sudden influx of occupants, temperatures can rise quickly and become uncomfortable before thermostats can pick up the change,” Mr Tan said.
On the other hand, a modern climate control system with both IoT and AI capabilities would be able to integrate people counters
to instantly detect the increase of occupants. Taking into account complex patterns in air flow and occupant movement, the system can then pre-emptively activate the chillers at the right power to cool specific locations within the building.
Another area to benefit from AI-enabled IoT is in the realm of smart manufacturing in connected factories, Mr Tan said. “Many manufacturing processes are already adopting AI to tune numerous parameters. The use of AI optimises the production line for customised targets, allowing factories to be more versatile and flexible. The increased efficiency results in lower inventories and waste, thereby reducing costs,” he said.
The challenge of implementation
Even though AI and IoT have both matured in their respective fields, they are still considered pretty new technologies today. As such, adopting and implementing both at the same time is the biggest challenge faced by enterprises, Mr Tan noted.
“Many companies have data science teams capable of designing and building AI models. However, it is beyond their domain expertise to deploy these AI capabilities and integrate them into production,” he said.
Conversely, there are also companies that have invested in IoT infrastructure and built applications to take advantage of IoT sensing, but these applications may not have the ability to deploy the latest AI models.
These problems can be addressed with versatile and easy-to-use IoT integration platforms such as NCS’ unifAI, Mr Tan said. The one-stop IoT portal makes it easy for data scientists to build AIpowered IoT applications, allowing them to directly access live IoT data streams for data collection and deploy AI models into production.
Building blocks of a smart city
The significance of AI-powered IoT systems is wide-reaching and “not just a good-to-have”, Mr Tan emphasised. “The largest scale deployments of AI-powered IoT systems are going to be smart city projects, which governments across the world are pushing for in order to improve the lives of their citizens.”
Mr Tan elaborated that in the near future, virtually every aspect of smart cities will be transformed and enhanced by AI and IoT. These include public safety, transport, healthcare and entertainment, to name a few. However, existing systems were built to function independently of one another and moving forward, they will need to be integrated.
Thanks to the vast wealth of data and feedback collected in real-time, AI-powered IoT systems will have the capability of learning the intricate patterns of causality and correlation between the various sets of data captured, allowing them to then predictively optimise the operation of various aspects of a city.
“These systems are self-adapting — in addition to the appropriate actions and decisions, the AI is also ‘smart’ enough to make suggestions to users on how they can adapt to the latest changes,” Mr Tan elaborated. “From traffic throughput and energy consumption to law enforcement, the ultimate goal is to help to make smart cities better places to live and work in,” he said.