Know The Role of Data Science in 5G Network

Know The Role of Data Science in 5G Network Technology is advancing at a rapid pace. Things that were only a dream yesterday have now become a reality. In late 2017, 5G was introduced to make our lives smarter, not only by making us smarter but also by making our environment smarter.

Before we get into 5G and its impact combined with data science, let's first define 5G.

5G 5G is simply a new global wireless network standard. It was introduced following the introduction of 1G, 2G, 3 G, and 4G, where G stands for "generation." It was created to virtually connect everyone and everything, including machines, objects, and devices. 5G will impact almost every industry, from transportation to healthcare to agriculture to logistics and many more, thanks to features such as faster speeds, low to no latency, and superior reliability.

Let us now focus on data science and its role in 5G.

5G and Data Science Our lives, lifestyles, and how we live will be drastically altered by data science and 5G, which will enable connected devices and automation systems with real-time data exchange. Smart cities, self-driving cars, AR/VR, smart healthcare, massive IoT, and smarter AI are now a reality.

With such high data transmission speeds combined with the power of low latency and mobile edge computing (MEC), which means downloading and uploading data faster than ever before, the foundation for technological developments known as Industry 4.0 has been laid, allowing analysts to collect, clean, and analyze large data volumes in less time. For example, a 4GB movie that took 27 minutes to download over 4G will take only a few seconds to download over 5G. With the introduction of 5G and the incorporation of data science, we have even been able to make our networks intelligent. Network analytics will enable us to build a flexible 5G network by reducing operational complexity. The analysis of network utilization and patterns in real-time traffic data will be based on machine learning algorithms. Network Planning and Organization (NPO) will decide where to scale network functions and application services, which were previously an afterthought.

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Some of the key characteristics of Data Science in 5G for business drivers are as follows: ●

Mobile Edge Computing (MEC): The interconnection of devices such as sensors, gateways, or controllers supported by distributed systems enables real-time insights with actionable intelligence. The most important aspect is dynamic network slicing, which allows traffic prioritization based on slicing.

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Data Monetization: While the world will realize the full economic impact of 5G by 2035, the impact can already be seen today. For example, before 5G, the concept of self-driving cars was not even a possibility. With an estimated potential growth of $13.1 trillion in goods and services and 22.8 million jobs, only time will tell how 5G will affect the economy.

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Predictive Maintenance: As one of the most important and leading use cases of Industry 4.0, using AI to predict failures before they occur would aid predictive maintenance. For example, in July 2021, the Pentagon stated that they had equipped their prediction systems with the ability to predict disasters occurring in advance, thus buying time for assistance in that region.

However, with great power comes great responsibility. As a result, some of the key challenges that will be encountered while laying the groundwork for combining data science and 5G are as follows: ●

Data and High Speed for Data-in-Motion: The data pumped by smart healthcare or cities, self-driving cars, and large-scale industrial IoT will be in petabytes in a matter of minutes, necessitating super fast lightning support to read/write data. Also, the type of data (labeled or unlabeled) will be critical in determining which type of learning is required.

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Security: The concerns raised by Big Data about end-to-end security are critical in order to protect enterprise data or user privacy without compromising. As a result, establishing a solid 5G secure infrastructure is critical.

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Real-Time Insights: Even though having negligible latency by providing lightning-fast data transmission and multi-edge analysis is one of the critical requirements of 5G, real-time actionable insights are still a major concern in mission-critical applications like security surveillance, public safety, and emergency care.

As some areas of the network have yet to have experimented with, it is still a long-term vision to encounter the full functionalities of 5G and its impact when combined with Data Science. Nonetheless, the combination of analysis and 5G will disrupt the way of life by facilitating Industry 4.0 technology. The combination of advanced technologies like IoT and ML with 5G network services generates massive amounts of data, allowing for more than just real-time data analysis and insights. As a result, we can conclude that these

technologies, when combined with 5G, will play a critical role in enabling AI everywhere. To learn more about techniques of data science and AI in different domains, visit the data science course in Mumbai. Master the data science and AI tools by working on multiple projects.