All the devices and systems on which we make use of the internet are interconnected to the network provider and also to each other directly or indirectly in some way.
They exchange information, useful files and use Artificial Intelligence AI in the form of machine learning or the Internet of Things.
Key Takeaways
- IoT connects various devices and sensors, enabling them to exchange data, while machine learning analyzes data and makes predictions or decisions.
- IoT focuses on interconnectivity and communication between devices, whereas machine learning emphasizes the development of algorithms for data analysis.
- IoT applications are more hardware-centric, while machine learning applications are more software-driven and based on data processing.
Internet of Things vs Machine Learning
Internet of Things (IoT) is the network of devices that can communicate with each other through the internet. Machine learning is an artificial intelligence that uses algorithms to learn from data. IoT focus on connecting devices, while machine learning is focused on data analysis and prediction.
Internet of Things is a giant network that is a part of the internet and connects several devices and interlinked systems with each other and to their network providers. This helps in the exchange of useful media and files from system to system.
It is abbreviated as IoT. Machine Learning is a very wide field of study which deals with the implementation of human behavior in machines so that Artificial Intelligence could be enhanced in the machines and it requires the Internet of Things to work upon.
Machine Learning gives the computer the ability to learn users’ minds.
Comparison Table
| Parameters of Comparison | Internet of Things | Machine Learning |
|---|---|---|
| Meaning | Internet of Things is the way of linking the devices with each other and to the internet. | Machine Learning is a way of making the systems understand hardware, heir user’s psychology through AI. |
| Field | The Internet of Things is based upon both software and hardware models. | Machine Learning is strictly a software thing and includes algorithms. |
| Use | Internet of Things accesses and produces huge amounts of data stored in a company’s servers or cloud. | Machine Learning manages and uses the data to enhance user experience through Artificial Intelligence. |
| Nature | The Internet of Things has a predictable and believable scope. | Machine Learning is a software-based process and produces unpredictable consequences. |
| Scope | The Internet of Things is a different subject that includes support of Machine Learning and AI. | Machine Learning is a way to increase the power of the Internet of Things and extends its usage. |
What is the Internet of Things?
Internet of Things is abbreviated as IoT and it is the study of complicated systems and other devices including their software properties and interlinked devices to connect with the internet and access the web.
These devices also share information and files to enhance communication and build up a strong network with each other.
Internet of Things deals with both software and hardware features of a device and communicates with other devices to enhance interlinking with one another.
It has several applications like in cloud computing, machine learning, software development, the hardware used in computers, the study of wireless networks and their linking properties, and most importantly, Artificial Intelligence.
We use the Internet of Things in our daily lives also. It includes all the devices that share data and duplicate the data so that organizations and companies who own these user data benefit from it.
It has a wide scope and properties. For instance, the Internet of Things uses sensors to detect the data linkage and communicates with other systems to share or receive data according to the need.
In other words, it eases the job of humans but at the same time, also can be dangerous because it uses AI.
What is Machine Learning?
Machine Learning is a very wide and deep subject that has its aspects in the Internet of Things, the programmed features that we use in computer systems, and on the web.
Machine Learning is really important because it uses Artificial Intelligence and other software tools to imitate human behavior and enhances the user experience by showing them what they like and easing the difficulties of the user.
Machine Learning is a varying concept and does not include direct programming. It lets the machine or the software program in itself and supports the users to benefit us.
Every platform uses Machine Learning and Artificial Intelligence and is integrated with the data they have in them and also the data stored in servers and online cloud spaces.
They use manual and non-programmable data to analyze the subjects and it helps the machine program automatically. Machine Learning and Artificial Intelligence, in general, share several things in common.
They have even come up at such levels that if two AI potent robots are made to sit face-to-face with each other for several days, they may even come up by developing an all-new language. Machine Learning can even do wonders.
Main Differences Between Internet of Things and Machine Learning
- Internet of Things is a total scale of learning and using the internet on devices whereas Machine Learning is a way of using these devices efficiently for one’s own benefit.
- Internet of Things is based upon aspects like Artificial Intelligence, Machine Learning, Programming, and hardware devices whereas Machine Learning is based upon analysis and patterns of using data.
- The Internet of Things is a very big subject and has a large scope in grasping knowledge about systems whereas Machine Learning is not vast but deep in logic and analysis.
- Internet of Things uses OOPs and High-level programming languages whereas Machine Learning uses complex data algorithms.
- The Internet of Things connects the devices whereas Machine Learning analyses the devices.
- https://ieeexplore.ieee.org/abstract/document/7964681/
- https://ieeexplore.ieee.org/abstract/document/8424629/
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