We are fast approaching an era in which smart machines and big data gathering capabilities become part and parcel of global industries. Applications of AIoT, Artificial Intelligence of Things, being used today can be seen in most high-income residential areas and big businesses. While not as widespread as it is touted to be, adoption is increasing exponentially in developed countries.

The internet of things, as an umbrella term, represents a network of connected objects that each connect either to the greater internet or to your personal app. When we toss an AI algorithm and machine learning capabilities into the mix, we can then expect IoT smart devices to learn, self-improve, and adapt to changes based on their experience and those of other systems.

AIoT, or Artificial Intelligence of Things, is an integration between the infrastructure behind the Internet of Things and artificial intelligence technology. The mesh between IoT and AI leads to an enhanced human-machine interaction, data management and analytics, and an overall improved customer experience for IoT users.

With that said, here are the most common applications of AIoT seen today:

Autonomous Vehicles

Autonomous vehicles are perhaps the most obvious and widespread applications of AIoT today. Self-driving vehicle manufacturers such as Tesla use their thousands of vehicles currently on the road to gather millions of data points as they drive around both manually and automatically. They use this data to map out roads, refine their vehicle’s automated driving systems, and bolster their data pools to improve their products and create better ones later down the line.

Manufacturing

Perhaps the biggest adopter of IoT and AIoT today is the use of AI to improve the performance and efficiency of smart factories. Most factories in heavily industrialized countries already use embedded sensors to gather large amounts of data on the manufacturing process.

 Industrial and manufacturing robots are becoming smarter through the use of AIoT, which allows factory robots to learn patterns and predict disruptions, delays, and damages before they happen. Predictive maintenance and supply disruption is perhaps the biggest money savers for any manufacturer.

Retail

The data gathered by facial recognition cameras and other sensors can help map the path that retail customers take to the checkout line. Data such as this can help managers predict the occurrence of staff shortages and provide insight into customer behavior in the store to improve the retail experience and even plan store layout to get the most out of a customer’s visit.

Smart Thermostats

This is where modern applications of AIoT meet smart homes. Automated and AI-enabled temperature regulation saves you the most on the electric bill, but it could also, over time, learn what is best for human health by adjusting the house’s temperature based on the weather outside, the homeowner’s work schedule, and temperature preferences.

In the near future, the integration of WoT, or web of things, which is just IoT connected to the wider internet, will see even bigger transformations. In a fully AIoT realized future, the planet will act as a giant interconnected web of data gathering systems that autonomously improve upon each other by learning patterns and making connections that would take us, humans, months if not years of collaboration and research. 

It is not clear to most how IoT and WoT are related as the words internet and web are often used interchangeably. However, they are not the same thing and have extremely different applications on different scales. 

The internet of things (IoT), as we have covered extensively on Inside Telecom, refers to connected devices. Simply devices linked to your phone that you can control and regulate from afar, with some degree or automation.  

In a smart home, while it is possible to synchronize multiple devices together, it is made of multiple smart items that are connected to your phone, each with its own apps and different manufacturers and protocols.  

This is where the distinction between IoT and Web of Things (WoT) is seen, but to see how IoT and WoT are related, let’s ask the important question first. 

 What is WoT? 

The Web of things can be defined, at least fundamentally, as two or more linked systems of devices that can share data. It is a network of two or more groups of connected devices. 

Your smart home with all its appliances attached to your home internet from a network, but each of your smart devices still uses its own applications specific to the item and the manufacturer. Your smart door and smart fridge are not really connected to each other, just connected to you. 

Also, with such protocols enabled, your home could link to all the other homes in the neighborhood. A smart farm could link to the local weather forecast. Smart factories could be linked to their suppliers to predict delays, etc.  

That is what distinguishes IoT from WoT, it allows simplified and standardized interoperability between different vendors which makes larger-scale connectivity much easier. 

Whereas IoT refers to a system of connected devices, the web of things refers to a network of networks or a system of systems.  

Interoperability between different networks opens new possibilities for joint technologies to operate across vastly different domains beyond smart factories, homes, and buildings.  

Such protocols would enable large-scale connected projects to be built more reliably. Smart cities, smart ports linked to other smart ports across the ocean, and smart farms linked to weather forecasting stations for predictive irrigation. Such projects can help illustrate how IoT and WoT are related and will be applied in the near future. 

Summary: 

Where IoT refers to connected devices that together form an enclosed network, each of the devices is generally connected one way to the owner’s device and constitutes low-level sensors and devices. The WoT takes those systems and standardizes their operating protocols to enable interoperability, forming a system of systems. 

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It is estimated that the number of active Internet of Things (IoT) devices will surpass 75 billion in 2025, according to Statista, and the market size of IoT is estimated to reach over $2 trillion by 2027, according to Business Insider.  

That is a staggering number, and no doubt, connected devices and the internet of things will generate trillions of dollars in economic value as we head into the 2020s.  

Home cameras, smart fridges and coffee machines, automated vacuum cleaners, and heat regulators; this is only the beginning. And that’s just home devices. Industrial, medical-smart devices and more are all proliferating rapidly, with 48 percent of businesses admitting that they cannot detect security breaches until it is too late.  

IoT devices are meant to make our lives easier and our businesses more efficient. With such numbers and rollout speed, is it any wonder why people are worried that their smart products, connected devices, and IoT devices could be hacked or compromised?  

In most cases, hackers use routers as a gateway, and the vulnerabilities often lie in the device itself, with little the customer can do about it.  

Whether it’s a home network or an industrial one, any given set of devices are all connected to the same network, and it only takes compromising one of those devices to access them all. In many cases, knowing the manufacturer of such a device is a threat that a hacker can face.  

Someone with access to your stove can cause it to overheat and start a fire or use your security cameras to spy on you or see when you’re not home to rob you.  

On a larger scale, a shady competitor can hack into a business’ production lines and cause all kinds of mayhem. And if a power plant is hacked, it could cut power to an entire city since hacks like these can be used for sabotage, disruption, or large-scale ransom. 

One solution to this problem is to use open-source IoT software so that a single manufacturer does not bind the code.   

As IoT technology becomes more mainstream, more solutions are being developed both on the software and device levels. Manufacturers will eventually be forced to adhere to stricter regulations. Large companies such as Amazon and Google will, hopefully, be compelled to make their data gathering and security rules as transparent as possible to their customers and adopt a ‘privacy by default policy. This will give the customers the choice of providing their data for “an improved experience.”