As technology use has grown exponentially during the pandemic, generating unprecedented volumes of critical business data, businesses are turning to the edge to help accelerate growth and drive business transformation, a survey from Intel has revealed.
Intel’s new report, “The Edge Outlook,” identifies edge computing as a critical factor that businesses must harness to both successfully navigate and understand data both now and into the future.
According to the report, many organizations are facing very real data processing challenges. For example, it’s impractical to send the sheer volume of data now being created back to the cloud for processing due to latency issues. This is where edge computing can play a critical role in driving efficiencies and underpinning the future growth of business.
Intel said that Edge computing is already bringing digital services to the next frontier working in synergy with critical technologies like AI and 5G. It can play a critical role in driving efficiencies and underpinning the future growth of business, said Intel.
The survey found that businesses are realizing that the edge is integral to unlocking future innovations, with 76% of respondents indicated that identifying “the ideal location” for data process was a challenge.
Looking at key verticals, the study noted that data analysed at the edge corrects massive amounts of inventory distortion, while making supply chains and product development incredibly efficient. Intel said the edge is providing retailers with real-time consumer behavior analysis, empowering them to deliver more personalized experiences.
Key industrial edge applications, including AI-based robotics and machine vision, are also being used to validate features and check for defects, helping to deliver the highest-quality product possible. Intel also observed that such edge deployments have helped its customer Audi to boost weld inspection speed by 100 times with 18ms of latency. Also, labour costs are said to be down 30-50% at its site in Neckarsulm, Germany, one of the company’s two principal assembly plants.
Edge computing is also helping to deliver a higher quality of care and clinical efficiency in healthcare by enabling frequent patient monitoring and data collection, integration with electronic health records and AI-powered patient data analysis, said the report. Deep-learning inference is used in image-based diagnostics to speed the detection of health issues and save lives. With edge technology, Philips managed to speed CT scan imaging by 188 times without needing to add hardware acceleration.
Edge in telecoms was found to be driving network and operational efficiency, with machine learning helping operators to increase efficiency to meet rising service level expectations while reducing costs. Intel said that with AI and analytics-based engines, operators are able to intelligently manage 5G networks to achieve key network KPIs, network automation, energy savings and operational flexibility to serve a wide variety of 5G and edge use cases.