Are you interested in knowing real-life edge computing use cases?
Edge computing is helping businesses overcome the drawbacks of native cloud computing architecture that become prominent with an influx of big data.
Edge computing refers to the data collection and processing near or at the data source instead of a remote server or cloud. 5G technology improves edge computing implementation resulting in low latency, increased reliability, and real-time processing.
According to the research, the global edge computing market will reach a value of USD 116.5 billion by 2030, growing at a CAGR of 12.46% from 2022 to 2030.
In this article, we will highlight some of the real-life use cases for edge computing. Let’s start.
Edge Computing Use Cases
Edge computing use cases are growing with the popularity of the technology. We have listed 10 of the prominent edge computing use cases below:
Remote monitoring of patients is very common now in the healthcare industry as it assists healthcare providers and patients. Healthcare professionals can check on their patients remotely, and patients can avoid hospital visits.
All this is possible through wearable devices and the latest technologies like artificial intelligence. However, the processing of huge healthcare and patient data from connected devices is a significant challenge. The high latency to transmit data and security issues cannot be tolerated in healthcare solutions.
Edge computing offers an attainable solution to the problems faced using cloud servers placed in remote locations.
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Implementing Edge computing allows instant processing of data at the network edge like a hospital site or a patient’s room, sending real-time notifications to healthcare providers regarding unusual patient behavior, etc. Moreover, the local data processing in edge computing applications makes the process more secure too.
A million devices are connected in the industrial and manufacturing sector through IoT technology. All these devices collect sensory data, but not all of it is required to store on a central cloud server. The process of sending and storing huge data can be expensive.
Edge computing helps to efficiently process this data, discard what is useless and send the required data to the remote server in a corporate data center for storage and further processing.
Edge computing also helps with the predictive maintenance of manufacturing equipment. As it brings data processing closer to the data source, which is machinery, real-time processing, and analytics with technologies like machine learning help to detect faults in production lines before they even occur.
Smart manufacturing, intelligent operations, energy efficiency utilities, etc., in the manufacturing sector, are assisted by IoT sensors and edge computing. Edge computing carries out rapid processing at the endpoints addressing problems and providing real-time analytics on-site.
According to the report by Gartner, there were 0.4 billion IoT endpoints in the retail and wholesale sectors in 2020. This includes a Google search by someone looking to purchase a certain product or Siri sharing the genre of the movie someone is going to watch.
However, all this information is useful if businesses are able to process them in real-time and utilize it in the form of personalized user suggestions and marketing messages.
Edge computing helps instantly process the information on the device and provides insights into user activity.
Open Retail Initiative by Intel is an example of an open-source framework for edge computing that businesses can deploy and integrate with their own systems to process huge real-time data in-store and online.
Autonomous vehicles make a prime use case of edge computing. They produce huge data that need to be processed instantly to prevent unsafe delays. According to research by Morgan Stanley Global Telecom, an autonomous vehicle can produce more than 40 Terabytes of data in an hour.
Imagine stopping suddenly in front of a pedestrian crossing, or communicating with other autonomous vehicles in immense traffic. High latency, connectivity issues with a remote server, etc., can be harmful in such scenarios.
Edge computing technology installed in smart vehicles enables instant communication and real-time data processing preventing delays and costs that occur while first sending data to a remote server and then receiving the processed data for further action.
IoT and edge computing can significantly improve the supply chain. Edge computing can be applied at each stage like manufacturing units, warehouses, distribution centers, etc. Edge computing in the supply chain can help businesses predict the market demand and figure out supply issues before there comes a serious gap in the supply chain.
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The benefits of having insights into each step of a supply chain lead to efficient operations, increased customer retention, and reduced expenses on operations.
In a cloud gaming environment, the game is processed and stored on remote servers instead of gaming devices. Cloud gaming requires consistent low latency and a stable connection with minimum jitters.
Edge computing with the 5G technology can greatly improve the situation by providing ultra-low latency and real-time processing capabilities. The gaming industry is exploring edge computing solutions like placing gaming servers closer to gamers to provide an immersive and real-time responsive gaming environment.
Smart homes rely on interconnected IoT devices and sensors that enable automation of nearly every system, from AI-enabled virtual assistants like Alexa, and home security systems, to the smart fridge and smart speakers.
All these smart devices produce a huge amount of data whose collection, processing, and a round trip between remote server and device can cause significant cost, latency, and delay issues.
Edge computing can make the process a lot more efficient and secure where the necessary processing is done locally without the need for data leaving the house premises and interacting with third-party services.
Basic commands like changing volume, thermostat settings, switching lights off and on, etc., can be executed instantly even if the connectivity with the remote server is down.
Edge computing technology can be used to manage traffic in a smart city effectively. It can assist traffic control authorities in better managing traffic through the instant processing of data collected through smart traffic controllers and sensors.
Edge computing platforms can instantly take into account the ground conditions and control traffic, like diverting vehicles from congested lanes to an alternative route.
The real-time management of the flow of autonomous vehicles saves costs of huge bandwidth and required latency.
Edge computing can immensely improve customer service across all industries, including finance, retail, banking, etc. It enables businesses to apply personalization techniques and do better marketing of their services through targeted ads. On-device real-time processing of user activity data helps to achieve this.
Edge computing also assists in implementing technologies, like augmented reality and virtual reality, that require faster processing and low latency. Alternatively, if such data is transferred to remote cloud servers for processing, the cost of meeting high bandwidth requirements is quite high.
Edge computing technology can help implement effective security measures in workplaces. There is a need for immediate action in case of a security breach, and using remote servers to process data from security cameras and other devices can cause harmful delays.
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Edge computing in on-site devices can help instantly process data and take the required security measures.
Edge computing also helps ensure employees’ safety, such as laborers working in industries. Edge computing enables instant collection and processing of data related to the workforce location, machinery operations, etc. A remote server slows down the process of monitoring environments and taking safety precautions.
Final Thoughts on Edge Computing Use Cases?
The above-mentioned real-life edge computing use cases show that edge computing technology assists where traditional cloud computing technology falls short with the emergence of big data.
Edge computing architecture fulfills requirements for low latency and high security for secure and faster data processing on edge devices providing real-time analytics. The edge computing use cases span all the major industries, including healthcare, retail, oil and gas plants, civil engineering, etc.
Are you planning to utilize these edge computing use cases in your business process and services? Edge computing can help you devise better marketing channels and implement efficient supply chains.
However, edge computing is an advanced technology. You will require a qualified team of professionals who are experienced in edge computing and supporting technologies. Read more on how you can build a successful software development team on our blog here.
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FAQs on Edge Computing Use Cases
The prominent use cases of edge computing are seen in healthcare, manufacturing processes, retail, etc., for predictive maintenance, faster operations, energy efficiency utilization, handling sensitive data, etc.
It is a distributed information technology model that enables businesses to collect, process, and analyze data closer to the data source instead of in remote native clouds. An edge platform brings data storage close to the device producing data.
Edge computing is used in scenarios where huge data is to be processed instantly for real-time analytics. The massive data transmission to remote servers for processing and data storage is difficult due to network limitations and huge costs. Moreover, delays can affect the user experience and, in some cases, the safety of the human environment.