Benefits and Applications of Edge Computing

Edge computing can meet future demands of the Internet of Everything(IoT)applications because of its exceptional benefits,and it has already begun.Edge computing sets the stage for continuous innovation and multiple technology integrations.Applications of edge computing include the following.

Edge Computing in Smart Homes

Smart applications,such as security alarm controls,lights and TV switches,are increasingly part of home life with the growing popularity of IoT.Many controllers and sensors are deployed in the home to operate these smart apps.Edge computing drives the data processing function for privacy protection so that the home gateway is the limit to most computing resources and confidential data cannot be shared.

Edge AI delivers optimized intrusion detection and indoor placement for greater precision and minimal latency than cloud computing.For voice identification,semantic language comprehension and processing,smart speakers connect to the cloud,resulting in unauthorized access to one’s private home data.

Edge AI also supports a better home entertainment experience as the system recommends customized services without the need to upload user experiences to the cloud.

Edge Computing in Agriculture

AI at the edge also benefits agriculture.Besides their use in drones,IoT-based edge computing is essential for precision agriculture.


Dangerous and impassable areas can be accessed using drones that capture unique pictures from a bird’s eye view.Drone use is growing,and it is commonly applied in mining and precision agriculture.

Public Safety

The camera terminal’s computing power is enhanced to make facial recognition features independent of the cloud server,saving on bandwidth resources and image upload time.One of edge AI’s crucial use cases is real-time video analysis.When it is performed in the cloud,time lags and congested data traffic are typical.With the advent of edge AI,part of the work is transferrable to edge nodes.

Edge Computing in Healthcare

Edge computing in healthcare is primarily essential for smart wearables and pre-hospital emergency care.Medical technology and terminals continue to diversify as healthcare awareness grows,offering multiple use cases for edge AI.With edge AI,dual real-time communication lines between hospitals and ambulances are possible,facilitating actual-time image and natural language processing for efficiency and precision.

Smart Cities

With the continuous expansion of city scales,data is shared geographically,and there is a need for edge AI models to monitor and intelligently control latency-sensitive devices.As edge computing powers supercomputing and large-scale infrastructure capabilities,low-latency deployments can be achieved,while high-latency ones can be executed on edge nodes.

Autonomous Vehicles

Efficiency and safety are the mainstays of autonomous vehicles,reducing accidents and avoiding traffic congestion.The Internet of Vehicles comprises cellular networks,edge computing and AI working as independent technologies.Edge computing delivers low latency,rapid data transmission and more,facilitating autonomous driving.Intelligent transportation is an offering of AI.Edge AI optimizes vehicle performance and facilitates target monitoring,precise positioning,instantaneous decision making and astute perception.

Smart Factories

Next-generation smart factories employ machine learning and sophisticated robotics,software services and industrial IoT to boost production quotas and enhance efficiency under the Industry 4.0 Model.The systems respond rapidly,rectifying inconsistencies and troubleshooting production lines to avert serious complications.Edge AI can substantially improve efficiency and eliminate human errors by applying sensors and monitors to control and manage production.

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