Edge computing is a new approach that looks at where and how data is accessible and exploited to improve organizational performance, cost, and efficiency. In recent years, there has been a substantial increase in the adoption of edge computing. Companies must store an inflow of data in consolidated and cloud storage solutions as IoT applications proliferate. They are, however, reliant on edge because of the latency issue.
The volume of information stored at the edge is growing faster than the amount of data kept in the core. As the economy grows more networked and businesses adopt new technologies such as AI, they will face tremendous data growth. By 2025, artificial intelligence, analytics, and deep learning will drive 44% of data created in the core and edge, with a growing number of IoT devices providing data to the enterprise edge.
“Edge will play a crucial role by storing the key data and enabling latency-sensitive requests from endpoint transactions and services. Hence, as more data gets stored, it will become capable of computing functions. The edge will further enable distributed computing to perform real-time and more accurate analysis of streaming data”, said Sameer Bhatia, Director of Asia Pacific Consumer Business Group, and Country Manager for India & SAARC, Seagate Technology.
Use cases of Edge AI
Edge AI is a term that refers to the integration of edge computing with artificial intelligence. Edge computing is a distributed virtualization technology that relocates computation and storage arrays closer to the device’s location. Artificial intelligence algorithms process data created on the device, whether or not it has an internet connection. This permits data to be analyzed in a matter of milliseconds and provides a real-time response.
“The capability to run MLOps (Machine Learning Model Operationalization Management) on the cloud and publish a selected version to edge devices through a technology like AWS Greengrass is disrupting different industries, including manufacturing/industrial and healthcare” mentioned Rahul Mahajan, CTO, Nagarro.
Using Edge AI, we are helping our retail customers do better warehouse audits, and improve in-store customer experience through solutions like the endless aisle, virtual try-on, smart shelf planning, etc.Rahul Mahajan, CTO, Nagarro
He further explains how their organization uses edge computing to improve autonomous vehicles reaching their destination in safer and faster ways- “Using Edge AI, we are helping our retail customers do better warehouse audits, and improve in-store customer experience through solutions like the endless aisle, virtual try-on, smart shelf planning, etc. Similarly, 5G has improved the device communication speed dramatically, enabling infrastructure to capture micro events in real-time”.
AI-powered diagnostic models can identify possible issues in scans, X-rays, and other pictures, prioritizing them for radiologist or physician assessment. With real-time imagery and analytics enabled by edge AI, this significantly improves triaging and clinical support. Edge computing is now being utilized to remotely monitor the patient, automate healthcare delivery, apply AI to improve diagnosis speed and accuracy, track the vaccination supply chain, and much more.
“An example of a basic edge solution comes in the form of a wearable health monitor. It can analyze data locally like heart rate or sleep patterns and provide recommendations without a recurring need to connect to the cloud”, Vineet Aggarwal, CIO, Paras Healthcare Group says.
Some of the critical advantages of Edge AI:
- Privacy: Edge AI provides a foundation for protection as data processing activities occur at the edge or near the device. There is a significant likelihood of security and data privacy when data is created and processed at the exact edge location.
- Lesser power consumption: Edge AI will lower the frequency of to-and-fro connections with cloud data centers, removing the need for high energy consumption.
- Lower internet bandwidth: The data created by billions of devices necessitates a large amount of internet bandwidth to handle this data from cloud data centers. Edge AI significantly reduces the amount of bandwidth necessary to process information at the edge.
Richa Babbar, Director, Edge & Ecosystem Development, Web Werks Data Centers adds, “2021 has witnessed more cyber attacks as compared to last year and the number is likely to grow”.
Edge computing opens entry points for hackers for a data leak. This forces a greater need for security talent who can continuously test, update and patch any security systems in place while also monitoring all devices to ensure any licensing or warranties are up to dateRicha Babbar, Director, Edge & Ecosystem Development, Web Werks Data Centers
Trends for 2022
According to Seagate’s Rethink research, IDC projects that the worldwide datasphere will expand to 221 zettabytes by 2026 and that the volume of data rapidly transported from edge to core would increase from 8% in 2020 to 16% by 2022.
The potential of edge computing solutions ranges from basic event filtering to complex-event processing or batch processing. Edge computing solutions come in different forms.
Edge computing has gotten a lot of interest since the pandemic because of its ability to facilitate digitization and drive key processes in remote locations while avoiding network latency difficulties. Some of the major trends in Edge Computing that have been observed are as follows:
- IoT enablement: IoT systems collect real-time data from sensors, which is needed for essential decision-making. Because sensors have limited storage and computing power, the IoT device links to the edge device, which serves as a gateway for connectivity with corporate systems. The edge device serves as the foundation for secure communications. Furthermore, it gives judgments when data from sensors is required to be delivered to the main company data repository, as the data may not be relevant in decision-making at times. Smart city implementations are a classic example.
- Smart consumer electronics: Our devices are growing smarter as a result of edge processing at the component level. These electronics contain algorithms that enable auto-switching off and on, alarms or notifications for critical maintenance, and so on. Air conditioners, TVs, refrigerators, microwaves, washing machines, and other home appliances, for example, have several functions that make use of cutting-edge programs. Another illustration is smart wearables that warn us when our health is worsening.
- Security: Edge devices, such as security gates, enable security frameworks to improve device security. They hold authentication data such as signatures and algorithms that authenticate the real-time information for access to protected areas by a legitimate user.
- 5G specific services: Consumers will benefit from extremely fast data access thanks to 5G. By combining 5G connectivity with edge computing, organizations can achieve real-time parallel processing and data merging. This enables virtual reality implementations such as video call-based remote elevator maintenance using edge-based programs.
- Distributed storage networks for Web 3.0: The use of autonomous consensus protocols and shared ledger technology for new ways of storing data in decentralized file networks is gaining traction. Organizations anticipate that these storage networks would one day serve as the foundation for Web 3.0. However, the capacity of the decentralized storage networks will need to expand in order to accommodate hundreds of petabytes of data.
- Increased use of multi-cloud strategies: A multi-cloud strategy enables enterprises to more easily mix services and resources from numerous cloud providers to boost the flexibility and availability of diverse applications and services such as StaaS(Storage as a service), SaaS(Software as a Service), and CaaS(Container as a Service). However, this increases the complexity of infrastructure, security, and cost for organizations.
Connectivity is vital in every data center deployment, but it is more important at edge facilities, which require continuous connectivity with global reach, cloud platforms, and corporate central infrastructure. At our data centers, we have prioritized the network and connectivity layers, providing maximum redundancy with our own fiber trenches and single-hop access to all major Internet trades, internet providers, cloud providers, delivery networks, and Telcos.
“Additionally, with the advent of IoT, connected mobility, smart cities, and more, low-latency networks with high bandwidth will be critical. For instance, OTT players will use Edge computing for caching their content for faster delivery to users”, said Nitin M. Jadhav, EVP & Head – Solution Engineering & Network Services, Yotta Infrastructure.
5G and edge are complementary technologies. Edge computing, particularly on 5G networks, enables faster and more extensive data processing, resulting in faster reaction times, deeper insights, and improved user experiences.
“5G is capable of reaching speeds up to 20Gbps and supporting up to million devices per square kilometer while providing around 1ms latency. This is upwards of 1000 times faster than 4G – Telcos had to put a lot of restrictions with 4G. In a way, 5G can be the true foundation for IoT & Edge ”, observes Sridhar Mantha, CTO, Happiest Minds Technologies.
Industry 4.0 can achieve IT-OT convergence since Edge can include all IT systems as well as Industrial systems – these can include telematics, asset tracking systems, computer vision applications, etcSridhar Mantha, CTO, Happiest Minds Technologies
A balance can be struck in the industry of media and entertainment between innovative offerings, resource optimization, and improved working conditions. Businesses can speed up the processes of consolidating and mainlining high volumes of data from different storage devices with predictable, consumption-based pricing and flexible interfaces from high-capacity edge storage solutions while scaling to meet evolving needs without making large infrastructure investments upfront.
Oil and gas service providers deliver edge computing capabilities at remote facilities, allowing oil and gas firms to realize the full potential of IoT applications on offshore platforms. According to a study, over 1 terabyte (TB) of data is created on an oil rig every day, yet only 1% or less of this data is exploited as insights to increase operational efficiency.
As organizations develop, the requirement to be connected to the ecosystem becomes increasingly important for faster innovation and growth. The network edge is the new focus, providing an agile mechanism to connect with the cloud, internet exchanges, and the larger ecosystem within the data center. Businesses may host data and have direct access to it with edge connectivity and colocation without worrying about cloud egress fees, which can add up over time as customers’ data expands.
This UrIoTNews article is syndicated fromGoogle News