Coronacrisis accelerated ML and AI in the IoT: consequences

This is a 40% growth within the Internet of Things domain


Coronacrisis accelerated ML and AI in the IoT: consequences. Source:

The use of Artificial Intelligence and IoT Machine Learning services has significantly increased. The two services have a revenue projection of US$3.6 Billion in 2026.

The coronavirus pandemic affected many economic sectors. However, the IoT data analytics sector was less affected. Most emerging native data-enabled vendors benefitted from the pandemic, with industries trying to remote most of their operations. This in turn led to high demand for solutions such as asset management, predictive maintenance, asset visibility and remote monitoring.

Vendors now have easy access to ML and AI tools via different deployment options on-premises, on the edge and through Platform as a Service (PaaS) and Software as a Service (SaaS) platforms. The pandemic showed the importance of rapid deployment solutions such as SaaS.

Various firms such as Google, C3 and AWS successfully promoted their analytics capabilities as well as products through the creation of coronavirus centralized repositories data. Currently, the data lakes are un-monetized and also public.

In the future, the firms could create healthcare products using the data lakes. This could even be an initial test for data visibility and streaming analytics services. The pandemic also showcased ambitions in the healthcare industry such as biomedicine, pharmaceutical as well as telemedicine.

While data analytics and big data may not have a ready solution for COVID-19, IoT data has been instrumental in reducing pandemic-related anxiety. The data has also helped prepare infrastructure in case of new outbreaks and even monitor patients. While ML and AI usage has intensified during the pandemic, there has been a slowdown in greenfield AI projects.

We’ve reported that 4 out of 5 consumers worldwide would use biometric payment card.


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