Edge can converge through AI and machine learning in order to integrate insight into behavior that benefit companies and their consumers.

In recent years, the application of artificial intelligence in different organizations around the world has changed. As company-wide initiatives continue to dominate, cloud computing has become a critical part of AI growth. As clients spend more time on their computers, organizations are increasingly aware of the need to add critical computing to the user in order to support more clients. This is why the market for Edge Computing in the years ahead will continue to rise.

Instead of needing data to move from the source to a data center or cloud and back, Edge computing allows applications to run close to where data is produced, generating congestion that can not be endured by mission-critical operations. In addition, edge computing will open doors to innovation, improved security and enforcement, and automation when combined with artificial intelligence (AI).

Why Edge Computing?

According to Rapyder, "The speed at which data generates will never slow down. In fact, it's only going to see an upward trend by the day. As a result, businesses will be heavily relying on technologies like edge computing, in the future. An IDC research predicts that in 3 years, 45% of IoT-created data will be stored, processed, analyzed, and acted upon close to, or at the edge of the network. The research also points out that 6 billion devices will be connected to edge computing solutions.

By bringing in decentralization to cloud networks, edge computing has added to the many advantages that businesses can reap from data.

For example, disruptions can be limited to only one point in the entire network. Consider that there is a cyberattack that leads to a power outage. With edge computing, you can curb its impact on only the local applications rather than letting it spread through the entire network. That's just a one-use case. Every industry can benefit tremendously from edge computing."

Edge Computing's benefits are:

It provides improved reliability for high speed, reduced latency, allowing faster processing of data and delivery of content.

It provides better protection through the delivery of transmission, storage, and applications via a number of devices and data centers, making it impossible to recover the network from any disturbance.

It provides a much less expensive path to flexibility and scalability, enabling businesses to extend their computing power through a mix of IoT devices and edge data centers.

According to DevPro Journal, "Sastry Malladi, CTO of FogHorn and Senthil Kumar, FogHorn's Global Head and VP of Software Engineering, expect edge AI to make a significant impact on businesses and industries in 2021, for example:

• Edge AI tools will eliminate the need to rip and replace outdated legacy building management systems.
• Edge AI enables contactless health and safety monitoring in the workplace.
• Warehouse managers will implement mobile edge computing to keep up with increased orders.
• Automated safety monitoring will save businesses millions in workers' compensation costs.
• Greater adoption of video and other high-resolution, high bandwidth sensors increases the demand for edge AI."

What is the future of edge computing in a few years?

The future of edge computing is actively committed. Through the use of data, Edge can converge through artificial intelligence and machine learning in order to integrate insight into behavior that benefit companies and their consumers. Ultimately, it will be treated much like any other location where applications can be placed smoothly without compromises and with accuracy.