By Rahul S Kurkure
Edge computing is a distributed computing paradigm that brings computation and data storage closer to the sources of data. This is an architecture rather than a specific technology, which is a topology and location-sensitive form of distributed computing that improves response times and saves bandwidth. How it is gaining traction across the industries?
Data, as we all know, is the new oil of new-age businesses, delivering valuable business insights that enable critical decision-making. Today’s business processes and operations are all dependent on data gathered in real-time from IoT devices and sensors operating in remote locations. The traditional computing model which was constructed around a centralised data centre is today getting replaced by edge computing architecture.
With edge computing work is performed, with processes and analysis done nearer to the place where data is generated rather than sending raw data to the centralised data centre for processing.
According to Grand View Research, the global edge computing market size is expected to grow from $4.68 billion in 2020 to $61.14 billion by 2028, at a CAGR of 38.4% during the forecast period. This high growth can be attributed to the advantages offered by edge computing architecture, such as eliminating the interruptions caused in the data flow due to network congestion and near-zero latency achieved with time saved in the travelling of data to and from the data centre or cloud, especially for time-sensitive applications.
There are significant savings on bandwidth and costs as well. Adoption of industrial IoT solutions, 5G, AI and ML capabilities and tectonic shifts caused due to the pandemic across industries, especially large enterprises, will further accelerate the growth of edge computing.
Several industries can be revolutionised and bigger business benefits are achieved by leveraging edge computing architecture.
Automotive and Traffic Management
In autonomous vehicles, edge computing can help communicate in real-time and frequently by providing data on traffic, weather conditions or accidents. Traffic management systems can be optimised with intelligent transportation networks. Some edge computing features, like self-parking applications and lane-departure warnings, are already available. Batteries in Electrical Vehicles can be continuously monitored with edge computing helping in predictive maintenance.
Smart Cities are expected to be built on advanced intelligence and automation applications that leverage huge amounts of data, which have to be processed with low latency. 5G networks, along with edge computing can enable cities to address disruptions. Smart city municipalities can manage energy, air and water and conserve them with edge analytics. Building operations, such as ventilation, heating, lighting, and security can be monitored and controlled as well, with this technology.
Healthcare today is expanding outside the four walls of the hospitals and clinics. Remote-patient monitoring, virtual-patient visit and consumer wearables create huge volumes of data and have to be captured and analysed in real-time to deliver care anywhere by leveraging edge computing. On-demand content for AR and VR training programs with near-time insights into patients’ conditions can be provided with edge computing devices. Maintenance of medical equipment, patient confidentiality and data privacy can all be maintained, by processing data locally with edge computing.
Industrial IoT has numerous connected devices on the shop floor to collect data on the assembly line performance and the quality of finished products. Edge computing can support responding to production-related issues in near real-time and enhance the quality and efficiency of processes while reducing the need for human supervision. It can help in failure detection and predictive maintenance processes. Data captured from on-site cameras can be leveraged by edge computing to oversee workplace and employee safety, ensuring authorised access to restricted areas.
Edge computing technology, with its speed and efficiency, plays a key role in the future of agriculture and farming. Edge computing devices and IoTs can guide robots to perform automated tasks of watering and harvesting crops. Required data about the environment and climatic conditions can be gathered to make decisions locally, making the process more sustainable.
In addition to the above, edge computing solutions can be utilised for a wider variety of applications across other industries as well. Although in the early stages of growth at present, the technology has already begun to gain significant traction in business transformation.
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(Rahul S Kurkure is the Founder and Director, Cloud.in)
(Disclaimer: The views expressed in the article above are those of the author’s and do not necessarily represent or reflect the views of Autofintechs.com. Unless otherwise noted, the author is writing in his/her personal capacity. They are not intended and should not be thought to represent official ideas, attitudes, or policies of any agency or institution.)