Seamster, Topio Networks examine edge computing’s use in retail, healthcare and beyond

Through a taxonomy-driven AI platform, Topio says it is tracking more than 100 companies in the edge computing market and making the data available for analysis, free of charge. So far, there are 23 different vertical segments and 14 different technologies that apply to each of these segments in the US market, meaning there are 322 ‘micro’ markets, explained Gavin Whitechurch, co-founder, and EVP at Topio Networks.

The impracticality of moving data around, latency-critical applications, bandwidth issues, data residency, security, and growing network costs are driving interest in edge computing. Using these technological factors along with market factors like investment activity, innovation, and market interest (leveraging natural language processing techniques to measure interest across the internet), the company’s tools for evaluating edge opportunities are now available on the Seamster web site.

Automation via edge computing might not be feasible for all sectors

Based on their research, edge computing is in high demand, as are machine learning, robotics, and IoT, but as the markets keep developing, a priority shift is expected. For the manufacturing sector, legacy critical bandwidth is not the only significant driver, as data residency is also making the push for edge latencies such as robotics for automotive manufacturing.

Despite economic challenges, the automotive sector is expected to show some fast transformation, said Phil Marshall, Chief Research Officer at Topio Networks. Even though General Motors was one of the pioneers in adopting welding robots in 1969, the complexity and precision required in the industry are making automation in this sector complicated. Marshall explained there has been a noticeable push for automation and agility since 2016 when talk about a fourth industrial revolution emerged. And yet, Mercedes brought back people in the assembly line in 2016 and even Tesla’s Elon Musk claimed in 2018 that “excessive automation of Tesla was a mistake.”

“So, in other words, it’s not easy to bring automation and agility to the automotive sector. Companies like Tesla are really driving change in disrupting the traditional status quo, but not everything can be automated as basically because of the complexity and precision of that of the manufacturing process,” Marshall said. “When we’re considering solutions for this market, and in identifying those that show the most promise, they really do need to be targeted, understanding how the automotive manufacturing process works.”

Two markets with strong prospects are retail and healthcare. While physical retail is reinvented through automation, healthcare, especially considering the current COVID-19 crisis, is seeing significant disruption from market and technology developments.

IoT and healthcare disruption – and how edge will play a role

IoT and healthcare have the potential for many use cases “classified in the context of telemedicine, image analysis, patient monitoring, clinical operations, as well as mid medication management,” generated by increasing healthcare costs, Marshall added. Vertical integration and specialized, proprietary systems can introduce several challenges related to interoperability, security, reliability, and scalability which could make the infrastructure resistant to disruption.

Smart ambulances, for example, would make a great use case, provided players in this sector would get around the roadblocks. O2 and Samsung partnered to work on 5G connected ambulances for NHS to stream live video feeds and other information for remote triage and diagnostic treatment. Marshall believes this capability could be applied to other domains such as employment, residential centers for the elderly, and traffic management.

“Singapore is possibly one of the most advanced countries with some of the most advanced technologies in and around aged health care, which can also be parlayed into remote patient monitoring,” he said, as he discussed a solution developed by Tata consulting and a Singapore university to leverage sensors “whether it’s for personal monitor personal activities, to identify dangers such as electrical devices, to integrate with medicine, dispensing machines and so forth.”

Other AI sensors are used to measure gait and foot motion to detect stroked and cardiac arrests. In this case, local data residency is a critical aspect to ensure privacy and security. Although he doubted remote surgery would ever be possible, Marshall pointed out successful trials have already taken place in China and India through 5G technology and ultra-low latency connectivity, with the support of tech companies, including Huawei.

In the future, this type of advanced technology and edge computing acceleration can bring valuable contributions not only to global healthcare, but other sectors such as retail, manufacturing, and supply chain, especially in the context of a distributed workforce.

Article Topics

automotive  |  healthcare  |  market research  |  MobiledgeX  |  retail  |  Topio Networks  |  use case