LONDON, July 13, 2021 /PRNewswire/ -- The next wave of Internet of Things (IoT) analytics development willfully converge with the Big Data domain. Simultaneously, thevalue in the technology stack is shifting beyond the hardware and middleware to analytics and value-added services, such as Machine-Learning (ML) and Artificial Intelligence (AI). According to global tech market advisory firm ABI Research, ML and AI services are estimated to grow within the IoT domain at a CAGR of nearly 40%, reaching US$3.6 billion in 2026.
While COVID-19 impacted many industries, the IoT data analytics market has been less affected. In fact, many newly emerging cloud-native data-enabled analytics vendors have benefited from COVID-19. "Since industries are transitioning to "remote everything," out-of-the-box solutions for remote monitoring, asset management, asset visibility, and predictive maintenance are in high demand and exemplify market acceleration. Vendors, such as DataRobot, are now easing access to ML and AI tool sets through different deployment options at the edge, on-premises, and the cloud, and through consumption using Platform as a Service (PaaS), and Software as a Service (SaaS)," explains Kateryna Dubrova, Research Analyst at ABI Research. "All and all, the COVID-19 pandemic highlighted the importance of rapid deployment solutions, such as hardware agnostic SaaS."
Companies like AWS, C3, and Google also have been successful in promoting their products and analytics capabilities (tool sets and environment) by creating centralized repositories for COVID-19 data. Currently, these data lakes are public and are not monetized. However, it is expected that those companies will attempt to use the data lakes to create products for sale to the healthcare market in the future. From a technology perspective, the data lakes could be the first step for creating and testing data visibility, and streaming analytics services. COVID-19 has showcased the public cloud's healthcare industry ambitions expanding into pharmaceutical, biomedicine, and telemedicine.
Big data and data analytics might not have a remedy for the virus, but IoT-data enabled technologies proved essential to lessen public anxiety, to monitor patients, and prepare the infrastructure for new outbreaks. "AI and ML usage has accelerated during the pandemichowever, greenfield AI projects have seen a significant slowdown. The AI and ML in the IoT is at its early adoption stage, the lack of the development of data-enabled infrastructure prevented rapid adoption of the machine learning on operational level when COVID-19 accelerated," Dubrova concludes.
These findings are from ABI Research's IoT Data-Enabled Services: Value Chain, Companies to Watch, and Cloud Wars application analysis report. This report is part of the company'sM2M, IoT & IoEresearch service, which includes research, data, and analyst insights.Application Analysisreports present an in-depth analysis of key market trends and factors for a specific technology.
About ABI ResearchABI Research provides strategic guidance to visionaries, delivering actionable intelligence on the transformative technologies that are dramatically reshaping industries, economies, and workforces across the world. ABI Research's global team of analysts publish groundbreaking studies often years ahead of other technology advisory firms, empowering our clients to stay ahead of their markets and their competitors.
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SOURCE ABI Research
Original post:
IoT Machine Learning and Artificial Intelligence Services to Reach US$3.6 Billion in Revenue in 2026 - PRNewswire
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