Edge Computing Applications in Industries

Edge computing applications in industries, edge computing in farming, healthcare, smart cities, cloud gaming, transportation, network optimization

APPLICATIONS OF EDGE COMPUTING IN VARIOUS INDUSTRIES

The Goal of edge computing is to move computing activities as close as possible to the data source. It employs local infrastructure to process data rather than depending on remote data centers so it is adopted by various industries.

Edge Computing in Smart Manufacturing

Industry 4.0 is now facing many significant barriers that are impeding its progress. Many of these issues can be overcome by using computing at the edge.

Benefits of Edge computing in industry 4.0

Reduced latency: Sending an operational request to a data center consumes more time and also waits for a response. Edge computing has the capability that reduces latency.

Reduced storage costs: Using local storage might be difficult, while cloud storage can be costly. In smart manufacturing, there are numerous amounts of data generated by sensors, which requires a lot of storage as well.

Enhanced cyber security: For smart factories, cybersecurity is a top priority, as beneficial as the Internet of Things is, the addition of additional devices to the network means more possible access points for cybercriminals.

Manageable data analytics: The next industrial revolution is built on the foundation of big data. One of the most important benefits of the IoT is its ability to increase data analytics.

Improved compatibility: The improved compatibility of an IoT network find its potential. Finding compatible devices is a barrier to smart manufacturing’s growth.

Edge Computing in Farming

The farms are cultivating crops indoors without the use of sunlight, without the requirement of soil, or chemical pesticides. This process reduces grow times by more than 60 percent using sensors enables the business to track water use, nutrient density, and determine optimal harvest. Data is captured and analyzed to identify the effects of environmental factors and continuously updating the crop growing algorithms and make sure that crops are harvested in peak conditions.

Edge Computing in Healthcare

Healthcare helps to bring medical software and services to remote rural areas. Healthcare suppliers can access essential data about their patients consistently instead of associating with fragmented databases. The healthcare industry has dramatically expanded the number of patient’s data. These data are collected from devices, sensors, and other medical equipment that enormous data volume requires edge computing to apply automation and machine learning to access the data. Ignore normal data and identify problem data so that clinical can take immediate action to help patients avoid health incidents in real life. Medical devices themselves have native symbol presses information diagnosis or treatment. These devices depend on transmitting data to the cloud before making decisions.

Edge Computing for Smart Cities

Without edge computing smart cities is impossible to collecting information to do fundamental processing. Combined with the rising number of self-driving vehicles and Internet of Things technology, smart cities use benefits in an urban environment. The whole edge computing applications rely on the devices/ gadgets collecting data to process the tasks.

Edge Computing in Cloud Gaming

Cloud gaming companies use edge computing technology to build edge servers to reduce bandwidth and enhance responsiveness for gamers. The cloud rendered and execute the game scenes or videos transferred to clients over the internet running on devices. The terminal devices such as light-weight tablets, phones, virtual reality glasses, etc. This type of streaming is also eliminating latency issues because data is transferring from the cloud.

Edge Computing in Transportation

Intelligent transportation networks improve traffic management. Vehicles that use edge computing technology can interact more efficiently as they can communicate with each other to send data on accidents, weather conditions, and traffic. Autonomous vehicles could produce anywhere from 5 TB to 20 TB of data per day. Sensors installed in vehicles gather information about location, speed, vehicle condition, road condition, traffic conditions. While the vehicle is in motion, the data must be collected and analyzed in real-time using edge devices rather than the cloud. This requires onboarding computing each autonomous vehicle becomes an edge.

Edge Computing in Augmented Reality devices

Wearable gadgets like glasses and headsets are used to make this effect. The innovation behind this technology anticipates devices to process visual information and visual components continuously.

Edge Computing in Virtual Assistant

Edge computing architecture brings into the systems that provide the organizations can improve through performance in termination activity. Virtual assistance has the ability to sending, preparing and data requests to the concentrated server. The multiplication of localized data servers for edge computing makes it simpler to extend their network reach and benefit as much as possible from their data assets.

Network optimization

Improve network performance by measuring the performance of user traffic. Edge computing is used to guide traffic across the network for best traffic performance.

 

What are the challenges of Edge Computing?

Due to the growth of IoT devices connectivity of edge computing faces low-latency network limitations. Edge devices are critical to designing with poor and irregular connectivity.

IoT devices are very insecure. So it is vital to design an edge computing deployment that will emphasize power device management. Such as policy-driven configuration enforcement as well as security in the computing and storage resources including factors such as software and patching updates with special attention to encryption in the data at rest in the flight. Data life cycles the main problem with today's data is that there is so much unnecessary data. The data involved in real-time analytics is short-term data that is not kept over for a long time. A business must decide which data to keep and what to discard once analyses are performed and the remaining data must be protected under guideline policies.

What are the companies that are using edge computing?

These are the top companies that are using edge computing for a very long time.

·       Intel

·       IBM

·       Amazon

·       Hewlett Packard Enterprise

·       Red Hat

·       VMware

·       Vodafone

Edge and quantum computing was the only accelerated technology in 2021. In this era, new and upgraded technologies like edge and quantum computing are proceeding as they aid in the advancement of organizations more than manual work.