IoT and Machine Learning

Internet of Things (IoT)

The Internet of Things (IoT) is a system that enables data exchange between devices through the internet. This data exchange is categorized into three groups: M2M (Machine to Machine), M2P (Machine to People), and P2P (People to People). With IoT, our lives have become significantly easier, and we can see its widespread use in examples like smart cities, smart transportation, and smart home appliances. Even today, this system is widely used, and it will become indispensable in the future.
 

Machine Learning

Machine learning is a branch of artificial intelligence and computer science that involves learning from existing data, testing these learning models, and predicting future data outcomes. Let's explore where machine learning appears in our lives: it is present in recommended products on online shopping sites, in posts that appear on social media, in the banking and finance sectors, and in many fields such as healthcare and education.
 

The Harmony of IoT and Machine Learning

The Importance of Machine Learning for IoT

IoT devices interact with objects using a "gateway" network, enabling data transmission over wireless environments. Due to this, IoT devices and environments can become easy targets for cyberattacks. In the event of a cyberattack, there can be significant data loss or unauthorized access. Techniques like machine learning approaches based on data analysis are used to identify and detect anomalies in IoT environments. The advantage of this data-driven technique is that it operates faster than other methodologies and can address problems caused by unknown threats. For these reasons, machine learning becomes an essential part of IoT.

The Importance of IoT for Machine Learning

Data is the most crucial element for the realization of machine learning. This is where IoT comes into play. It helps by analyzing the data collected from the environment through sensors and objects and provides necessary results to the user. Machine learning moves from being a static state to becoming fully dynamic, making it more useful today and in the future.