How COVID-19 is shaping software and hardware trends

Technology to enable health and safety

COVID-19 has driven heightened awareness within society of the need to ensure our health and safety is protected. This is undoubtedly here to stay, with social distancing and increased hygiene standards forming an integral part of the “new normal” for the foreseeable future. This has, for example, led to increased adoption of existing contactless technologies and to tech companies harnessing other hardware and software developments to find innovative solutions. Here are some examples:

UV cleaning robots

Autonomous robots that can use UV cleaning may be the answer to the need to thoroughly disinfect public spaces more frequently. UV cleaning technology isn’t new, but its popularity had been limited by the risks associated with human use (it can damage skin and eyes and it is easy to miss spots). Recently, though, robots that can carry out UV cleaning safely (automatically shutting down if people are nearby), and accurately and autonomously (using simultaneous location and mapping software to navigate spaces without human intervention) have been developed. COVID-19 has accelerated their adoption by hospitals, public transport, hotels, warehouses and more.

Crowd control

For as long as social distancing continues, effective crowd control will be of the utmost importance. For retail businesses and other spaces where crowd size has not traditionally been tracked, occupancy monitoring presents a new challenge. Employing staff to manually count those entering and exiting a space is not sustainable. Instead, wireless sensor technologies are being used to develop automated tracking systems which can be deployed to monitor occupancy and provide real-time feedback. Again, the hardware and software underpinning this technology and its use for monitoring crowd sizes is not entirely new, but we anticipate that its expansion, development and adoption in new sectors will accelerate in response to COVID-19.

Contactless biometrics

Contactless technologies were already on the rise but COVID-19 has brought them more clearly to the fore. For instance, contactless payment systems have been adopted more widely and rapidly than might otherwise have been the case, and network effects are expected to encourage still further adoption. The use and development of contactless biometric solutions, in particular, looks set to explode, with authentication using facial and voice recognition having obvious health and safety advantages during a pandemic over some more traditional approaches.

The emergence of AI-as-a-service

While overall global IT spending is predicted to decrease 3-4% this year, adoption of AI and big data are predicted to increase. There is focus around AI as-a-service (AIaaS), which generally refers to AI software made available off-the-shelf with minimal tailoring required. This provides the advantage of companies not needing to develop their own infrastructure, technology and know-how. Various types of AIaaS offer machine learning frameworks that can be used to build models that are trained using existing company data. The tech giants, including Amazon Web Services, IBM Cloud, Google Cloud and Microsoft Azure, are leaders in this field.

This interest in AI, and AIaaS in particular, is driven in part by companies looking to build models to help accelerate the recovery from the widespread economic slowdown caused by the pandemic. Historical data (and related models) which were relied on might no longer be useful in navigating the impact of COVID-19. Current trends reflect how companies had to revisit risk and financial models following the 2008 global financial crisis.

Edge computing

Edge computing aims to bring data processing and storage closer to the devices where data are gathered, rather than relying on a central, and often distant, processing unit.

For example, business will often install security cameras which transmit live data feeds to a central office. When there are hundreds of cameras streaming live footage, this could create quality issues due to latency, and bandwidth use could be substantial. Edge-computing hardware and services can solve some of these issues by processing and storing data locally.

Global sales of edge computing services and infrastructure are predicted to grow 22.7% between 2019 and 2024, with sales expected to reach USD19.3bn in 2024. Despite COVID-19, recent research by Bain has showed that (of those surveyed) 95% indicated plans for deploying edge-computing and almost 75% intend to integrate edge-computing into their IT systems by the end of 2020.¹

COVID-19 has brought greater attention to the weaknesses of current network infrastructure. For example, Netflix in Europe reduced video quality following requests from governments to reduce bandwidth usage out of fear that too much stress was being put on broadband connections.

Whilst the use of digital devices and services is increasing, the transmission and storage of larger and larger volumes of data on limited bandwidth presents a significant challenge. It is expected that cloud service providers, software providers and network operators will continue to collaborate on the development of edge computing to help meet this challenge. The partnership between Verizon and Amazon Web Services on the development of edge computing technology in the context of 5g mobile networks is just one example.

¹https://www.globaldata.com/global-market-for-edge-computing-to-see-significant-growth-through-2024/