Some of the crucial factors that need to be considered while drawing a comparison between IoT vs AI are data learning, scalability, cost, and success rate of both technologies.
Updated 18 January 2024
VP – Pre Sales at Appventurez
If you’re new to smart home and business gadgets, you’ve certainly heard buzzwords like IoT, AI, and machine learning. And why not, given that these three disruptive technologies are all interconnected? However, as the world becomes more technologically advanced, we have arrived at the two ideal technologies for every business: IoT vs AI.
Top organizations are investing in IoT and AI technology to boost productivity and give a competitive edge, according to a new survey performed by SADA System. To unlock the full potential of IoT, both startups and established enterprises want to invest in ML & AI app development solutions. Some of the biggest IoT platform suppliers, such as Microsoft, Amazon, and Oracle, have begun to integrate AI elements into their Internet of Things programs.
However, the convergence of technology over time has blurred the distinction between the two. One of the most heated discussions among techies is IoT vs AI. In this essay, we’ll compare and contrast the Internet of Things and Artificial Intelligence in depth. It will assist you in selecting the appropriate technology for your company.
Let’s have a look at some crucial elements that you need to consider to understand the difference between IoT and AI before deciding on which technology is best and better suited for your business.
While talking about IoT vs AI, it becomes important to first understand the definitions of both the technologies. The Internet of Things is a network of connected devices that can sense, gather, and transfer data over a network without any human interaction. The function of IoT is based on the concept of everyday physical objects with the ability to communicate directly over an internet connection. Keep in mind that you can power up your business with reliable IoT app development solutions.
Artificial intelligence, on the other hand, is a way of machine learning (ML) in fact, which thoroughly examines the patterns and derives results effectively. AI is a result of collective predictive, continuous & perspective analytics. It won’t be wrong if we say it’s just mimicking human intelligence. You can also follow many top AI trends to cope with increasing users’ demands.
If you are thinking of using the best technology for your business, you should invest in AI application development.
In IoT vs AI, IoT provides the ability to connect and communicate with things from anywhere in the world, making its main purpose to let objects send and receive data over the Internet. On the other hand, the purpose of AI is to reassemble human behavior & intelligence in machines to make them act in a good way.
Like other platforms, Internet of Things technology is the internet working of physical devices such as sensors, actuators, and other important electronics that can communicate with each other without any human interaction while the main role of AI in business is to create technology to make people and machines work in collaboration.
You can also read about the journey of the automotive sector with IoT-enabled technology to make your automobile business successful.
In a nutshell, the Internet of Things means connected devices, sprawling networks, and huge amounts of data. From smart cities to cars, the world is becoming more interconnected with smart technologies every day. However, along with this popularity, there is more risk regarding data hacks and cyber-attacks. So, you need to be aware of the security challenges of IoT with their solutions to deal with them.
You can also consider them as top IoT trends for businesses to achieve great success in the future.
Examples of AI in pop culture usually include a basket of intelligent robots hell-bent on overwhelming the human race or at least a fancy theme park. Here are top examples of artificial intelligence:
No doubt, AI is everywhere and playing an active role in our daily lives. Whenever you log in to your Facebook, do Google research, shop online, or book a trip online, AI is lurking in the background.
Cost is a significant factor to consider while discussing IoT vs AI. Notably, IoT requires a group of interconnected hardware devices such as sensors, LED displays, controllers, and many more. If you calculate the costs of IoT with hardware, & software devices, you will get a sum smaller than $50 thousand. That’s how much it cost to build MVP versions of an IoT.
Whereas the price of artificial intelligence depends on the requirements. To calculate huge computations, this technology requires highly configured system architectures. Hence, it costs a bit more than IoT for renting or leasing remote services.
For a fraud detection coverage case, the price tiers are between ~ 100k- 300k$. Numbers significantly depend on the exercise – it all depends on the assignment scope, complexity, system necessities, and other elements referred to before.
If you are planning to start your business in the healthcare sector, you need to know about IoT healthcare’s future scope.
In the debate of IoT vs AI, artificial intelligence projects usually have a lesser success rate than the Internet of Things. IDC survey states that the highest success rates figures for AI were reported by 30% of the companies. For the rest, the failure rate ranged from 10% to 49%.
There are several reasons why artificial intelligence projects fail. Lack of data (whether it be quality or quantity) is one of the biggest reasons why AI technology is facing failure in comparison to IoT. Internet of Things projects might face elements of failure but overall most are successful.
According to reports, it is estimated that there will be 35.82bn IoT devices installed worldwide by 2021 and 75.44bn by 2025. Apart from this, there has been a great impact of IoT on mobile app development.
Worldwide AI (Artificial Intelligence) market size is expected to grow at a CAGR of almost 21% with $76.44bn during the forecasted period 2021-2025.
Let’s have a look at a graph of AI’s market statistics
When comparing the learning capabilities of two advanced technologies- IoT vs AI, Artificial Intelligence can be identified as a the system that learns from the mistakes or the background activities. It tries to develop itself to perform in a better way. The best example is Facebook.
On Facebook, if you have tagged some of your friends in formerly posted images and again you are posting your friend’s new picture, it will signify that you want to tag that buddy once again. It has been learned that the character with several capabilities is an “XYZ” person.
Alternatively, in the Internet of Things,
There are several sensors around us and each of them has a few facts flowing through them, and the identification information is being shared on the Internet. So, in IoT, the flowing records are being stored in an area & the identity is being processed. If you want that information, IoT shares the information with a person to help him with the help of analytics.
The Internet of Things is intrinsically more scalable than Artificial Intelligence thanks to its mobile-based cloud computing. The cloud structures and reduces the desire for extra challenging-stressed connections.
IoT lets data flow between several linked physical devices and AI helps make sense of the data. The Internet of Things produces a lot of data via a wide network of interconnected devices and most data is not even captured. It requires a way to intelligently analyze & gain information from this data.
Artificial Intelligence systems provide a means to do exactly this with minimal human intervention effort. This technology aims to gain information and make predictions by performing analytics with the aid of AI technology. So, while discussing the two advanced technologies- IoT vs AI, it’s clear that IoT won’t work without AI.
Internet of Things technology also supports cloud computing efficiently while a gateway is provided by IoT apps for business automation using cloud data management. Artificial Intelligence has brought highly strong cloud computing which enables machines to learn, think, and react like humans by creating human examples. AI mostly uses cloud computing to perform huge computations over a remote server called a cloud with high configurations.
During IoT vs AI discussion, it should be pointed that artificial intelligence is all about learning & behaving like a human, so it mainly relies on keen learning of algorithms that will be received from different sources to create human behavior into the system. On the other hand, IoT is all about creating a customized algorithm to manipulate the system’s functionality.
Let’s have a look at charts of both technologies’ benefits & drawbacks for a clear understanding of IoT vs AI:
Embark on the exciting frontier of AI & IoT, unlocking their transformative potential to enhance your business value, and Appventurez is your ideal destination! As a leading IoT app development company, we provide comprehensive Artificial Intelligence & Internet of Things solutions, enabling businesses to seamlessly integrate these technologies into their existing enterprise framework. Our specialized team comprises seasoned iOS & Android app developers with extensive expertise in the realms of Internet of Things and Artificial Intelligence. If you’re seeking a dedicated partner to navigate the intricate landscape of AI & IoT, Appventurez stands ready to guide you through every step of the journey.
We specialize in offering artificial intelligence app development services, assisting you in the creation of innovative and reliable AI and IoT applications that unlock the potential for new software possibilities. Our expertise extends to seamlessly integrating artificial intelligence and Internet of Things technologies, aiming to enhance operational efficiency and prevent costly unplanned downtime.
Whether you believe it or not, AI and IoT are the present & future. In this fast-growing world, both technologies are rapidly growing. So, amid the debate of IoT vs AI which is better, it has become essential for every business to incorporate both the Internet of Things and Artificial Intelligence into their business operations, not just to reduce human errors. Notably, it not just reduces human errors but also increases productivity and smooth the flow of business processes.
As said before, AI not only helps in making recurring tasks but also in learning, analyzing, and acting like human beings and maybe often better than them. While, IoT is a huge network of interlinked computing devices connected to the Internet. These devices can sense, gather and transfer data over a network without any human intervention.
In the final verdict of IoT vs AI debate, it can be said that together they bring in a connected level of intelligence which will make computers smart along with interconnected devices.
Individually, both the Internet of Things and Artificial Intelligence are the most powerful technologies. However, when you combine AI & IoT, you will get AIoT (Artificial Intelligence of Things). You can consider IoT devices like the digital nervous system while AI is the brain of a network or system.
Q. Which companies are highly using AI & IoT technologies?
Many established companies are investing a lot of revenue into AI & IoT technologies to enhance the workflow of their companies. Google, Amazon & Netflix are renowned companies that are using these technologies.
Q. What are the main contributions of AI & IoT in today’s world?
Ai & IoT have made a major difference in several areas such as self-driving cars, automated cutting machines, smart home appliances, and personal assistants in our smartphones, desktops, and other smart devices like Google Home and Alexa.
Q. Which languages are best for AI & IoT?
Java, Python, Golang & C are the best programming languages for IoT & AI development solutions.
Elevate your journey and empower your choices with our insightful guidance.
VP – Pre Sales at Appventurez
Anand specializes in sales and business development as its VP - Sales and Presales. He supervises the pre-sales process by upscaling on establishing client relationships. He skillfully deploys instruments such as cloud computing, automation, data centers, information storage, and analytics to evaluate clients’ business activities.
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