The Internet commenced as a medium to share files remotely. It didn’t take time to flourish as the most popular globe-spanning communication network for sharing information, messages, and all kind of data. With the evolution of technology, the internet is now the one-stop solution for everything. The Internet made the computers, and then the mobile phones, as resourceful as these technologies were never before. By connecting computers and smartphones with the internet, these desktop machines and portable devices have become a portal to the whole world, whether it be simple browsing, online shopping, communication and messaging, or other uncountable services and applications.
How could embedded devices have been left behind? In fact, the embedded electronics being confined to their particular applications need only low-bandwidth connections to use the internet. The Internet made these diverse electronic circuits useful ‘Things’, and their network over the internet is called ‘Internet of Things’. As computers and smartphones, embedded devices combined with the internet are much resourceful than ever and remotely manageable anytime from anywhere.
One other technology under development and the internet and internet of things (IoT) is Artificial Intelligence. Artificial Intelligence aims to make computing devices smart and autonomous. The AI attempts to program computers (controllers and processors) to learn from their environment and make decisions on their own without human interference. This technology is again seeing a convergence with the internet and the internet of things with the title ‘Artificial Intelligence of Things’.
What is AIoT?
AIoT is the combination of Artificial Intelligence and the Internet of Things. Where IoT aims to remotely facilitate to and fetch data from electronic ‘Things’ in real-time and store the data from connected ‘Things’ over a server for data analysis; the implementation of Artificial Intelligence within an IoT solution enhances the data analytics, enable machine learning, and make the connected ‘devices’ independent and autonomous. Artificial Intelligence within IoT systems can automate IoT operations, manage data and communication, perform real-time automatic data analytics, and improve human-machine interaction. The connected devices with their own brains will be useful in automating services and applications that rely on human input and interference. After all, internet-enabled thoughtful machines can make better decisions than ordinary humans. AIoT is a magnificent empowerment of machines, applications, services, users, and networked platforms.
The convergence of AI and IoT is mutually beneficial for both technologies. IoT benefits AI in terms of real-time real-world data, world-wide connectivity, and much realistic implementation. IoT gains from AI in better security, improved analytics, predicted information, and machine learning capabilities. IoT is making the data always available anywhere to the billions of embedded electronic devices, and AI is making that data smarter than ever possible. IoT can be used to infuse artificial intelligence into user programs, embedded chipsets, and edge computing.
The very first vertical that will benefit from the AIoT is mobile application development. Smartphones, wearables, and several other portable devices are ubiquitous and capable of hosting all sorts of applications and services. These devices already have internet, and artificial intelligence at the edge can render high-performance real-time hybrid applications that can automate tasks or assist users with the least dependence on cloud computers.
IoT vs AIoT
Many of you might still be wondering how IoT and AIoT are different. IoT only connects electronic devices with a computer network for real-time communication, data logging, and data exchange. It does not involve any data analysis or autonomous decision-making either at the cloud or the edge. AIoT adds artificial intelligence and machine learning algorithms to the edge or the cloud platforms within IoT infrastructure, so the connected ‘Things’ get a brain to make decisions of their own and automate operations without relying on humans. IoT is a brain-less network of pre-programmed reactive devices and cloud servers for data communication and remote management. AIoT is a network of proactive, intelligent devices with connectivity to regular or thoughtful cloud platforms. AIoT is a hybrid system implementation where artificial intelligence and machine learning are infused either at the cloud platform or the edge devices.
Scope of AIOT
Like the internet is ubiquitous, the Internet of Things is also ubiquitous. There is no vertical that is excluded from the span of IoT. Every electronic device in the future will be basically a ‘Thing’; it is consumer devices, self-driving connected vehicles, smart cities, or industry 4.0 devices. AIoT is an addition to the existing IoT infrastructure. The verticals that involve immediate applications of AIoT include hybrid mobile applications & services, cognitive computing in the consumer edge devices, smart home technology, and industrial automation. The future involves the convergence of artificial intelligence, machine learning, deep learning, 5G networks, and big data analytics with underdeveloped IoT infrastructures. The major verticals with AIoT implementation include smartphones, wearables, smart cities, smart homes, and the Industrial Internet of Things (IIoT).
AIoT Examples
Let us see how AIoT can be useful in different verticals with few examples –
Smart City – In a smart city, AIoT can be used to monitor traffic, manage traffic using real-time data, perform surveillance and security like identifying suspects or recognizing law and order problems, share infrastructure details and traffic updates with smart vehicles, manage routing for emergency vehicles and provide real-time assistance.
Smart Vehicles – In smart vehicles, AIoT can be useful for communicating with other vehicles, avoiding accidents, lane management, development of self-driving cars, routing and traffic management, parking management, anti-theft, and self-maintenance.
Retail – In retail stores, AIoT can be used to identify and recognize customers, analyze customer behavior, customize product selection, automate shopping and bill payments, automatically update offers and discounts to customers, and manage inventory.
Hybrid Mobile Applications – Hybrid mobile applications having artificial intelligence at the edge and connectivity to IoT networks can be used for real-time assistance, automate shopping and financial transactions, product research based on object recognition, traffic assistance, feature comparisons, etc.
Conclusion
IoT generates useful data in real-time from the real world. AI provides insights from the collected data. The combination of both these technologies for a shared goal is AIoT. Apart from AI, other technologies converging with IoT infrastructures are 5G and big data analytics. AIoT is an important upgrade to existing IoT architectures. It will help in providing predictive analytics from the backend while infusing cognitive capabilities to the edge devices. It will positively impact all verticals, particularly IIoT, hybrid mobile applications, smart homes, smart cities, and consumer electronics.
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