K
Kathleen Martin
Guest
In Asia-Pacific (APAC), edge computing is rapidly developing into an important frontier for enterprise innovation and competitive differentiation. Across the region, adoption is rising and usage will only grow moving forward, as consumers, businesses and governments continue to embrace Internet-of-Things (IoT) devices.
Edge computing refers to a distributed computing framework that brings enterprise applications closer to data sources. Unlike traditional models where computing power is centralized at an on-premise data center, edge brings computing closer to where data are being generated, enabling processing at greater speeds and volumes, and allowing for greater action-led results in real time.
For users, this means a faster and more consistent experience. For enterprises and service providers, edge means low latency, ultimately leading to reduced transmission delays, lessened bandwidth constraints, limited service failures, highly available apps and real-time monitoring capabilities.
Other benefits of edge computing include the ability to conduct on-site big data analytics and aggregation, which allows for near real-time decision making. Enterprises also benefit from reduced risk of exposing sensitive data since all of that computing power is kept locally. This implies better enforced security practices and easier regulatory compliance.
And since companies no longer need to take data back and forth between core and regional sites, edge computing allows companies to cut down bandwidth costs and increases their resilience as regional sites can continue to operate independently from a core site.
Today, edge computing is in use across many industries with most of its applications revolving around use cases that need low latency and fast response time, and which benefit from real-time analytics.
For example, in manufacturing, edge computing is used to monitor manufacturing processes and apply machine learning (ML) and real-time analytics to improve product qualities and detect production errors. In the construction industry, edge computing is mainly used for workplace safety to collect and analyze data taken from safety devices, cameras and sensors. And in transportation, edge computing allows autonomous vehicles to collect and analyze data while they are moving, in real time.
Continue reading: https://fintechnews.sg/64749/digital-transformation/rising-adoption-of-iot-devices-pushes-usage-of-edge-computing-upward/
Edge computing refers to a distributed computing framework that brings enterprise applications closer to data sources. Unlike traditional models where computing power is centralized at an on-premise data center, edge brings computing closer to where data are being generated, enabling processing at greater speeds and volumes, and allowing for greater action-led results in real time.
For users, this means a faster and more consistent experience. For enterprises and service providers, edge means low latency, ultimately leading to reduced transmission delays, lessened bandwidth constraints, limited service failures, highly available apps and real-time monitoring capabilities.
Other benefits of edge computing include the ability to conduct on-site big data analytics and aggregation, which allows for near real-time decision making. Enterprises also benefit from reduced risk of exposing sensitive data since all of that computing power is kept locally. This implies better enforced security practices and easier regulatory compliance.
And since companies no longer need to take data back and forth between core and regional sites, edge computing allows companies to cut down bandwidth costs and increases their resilience as regional sites can continue to operate independently from a core site.
Today, edge computing is in use across many industries with most of its applications revolving around use cases that need low latency and fast response time, and which benefit from real-time analytics.
For example, in manufacturing, edge computing is used to monitor manufacturing processes and apply machine learning (ML) and real-time analytics to improve product qualities and detect production errors. In the construction industry, edge computing is mainly used for workplace safety to collect and analyze data taken from safety devices, cameras and sensors. And in transportation, edge computing allows autonomous vehicles to collect and analyze data while they are moving, in real time.
Continue reading: https://fintechnews.sg/64749/digital-transformation/rising-adoption-of-iot-devices-pushes-usage-of-edge-computing-upward/
