Edge computing is a distributed, open AI architecture that features decentralized processing power by enabling mobile computing and Internet of Things (IoT) technologies. This minimises the need for long-distance communications between client and server, which reduces latency and bandwidth usage.
Edge computing is adopted by various industries. Some of its applications stand out in the following areas,
Oil and gas industry– Real-time remote monitoring plays a pivotal role in the oil and gas industries. Advanced machinery powered by IoT sensors is deployed at isolated sites to safeguard critical machinery and systems against disaster.
Smart cities– Smart cities will be nothing without edge computing technology. The edge computing devices are collecting information to do fundamental processing tasks, which is the core of smart city development.
Autonomous vehicles– Edge technologies can help autonomous vehicles to communicate frequently by sending data on accidents, weather conditions, traffic, etc.
Security– Installed edge computing devices identifies and flags unusual behaviour in real-time which eventually leads to counter actions as soon as possible, acting as a security surveillance system.
Cloud gaming– Cloud gaming is the new kind of gaming which streams live feed directly to devices. Cloud gaming companies use edge computing technologies to build edge servers close to gamers in order to reduce latency and provide responsive and immersive gaming experience.
Manufacturing– Edge computing allows industrial machinery without human intervention to make decisions. The decentralized design helps in minimizing time and costs. As the architecture for machine learning networks is developed by edge computing, robotics-driven manufacturing is also probable.
Financial Sector– Banks can build branches of general and white labels, assisted remotely using computer vision and edge analytics. This helps to provide consumers with financial banking products and services everywhere.
Healthcare– In healthcare, edge computing aims to speed up connectivity between machine-to-machine and machine-to-human interaction. Through spreading workloads at branch data centre sites, this processing process can also help bring medical software and services to remote rural areas.
Traffic Management- Improving real-time data is one of the best methods of optimizing traffic management systems. Intelligent transportation networks, in particular, for traffic management processes make extensive use of edge computing technologies.
Edge Video Orchestration– Edge computing resources are used by edge video orchestration to carry out a highly optimized delivery procedure for the broadly utilized yet bandwidth-heavy resource i.e. video. This is something that 5G edge computers will solve in the next few years.
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