As we start 2023, the IoT Analytics team has again evaluated the past year's main IoT developments in the global "Internet of Things" arena. This article highlights some general observations and our top 10 IoT stories from 2022, a year characterized by a skyrocketing inflation rate, ongoing supply disruptions, and a looming recession. The 4.4% global growth forecast for the year (from January 2022) was almost certainly not reached, and the outlook for 2023 has been lowered to a meager 2.7% (as of Oct 2022). The Nasdaq Composite, one of the key indices for technology companies, fell 33.1% in 2022. Against this backdrop, IoT 2022 markets held up somewhat steadily, with the number of connected IoT devices growing to approximately 14.4 billion (exact update coming in a few weeks) with roughly $202 billion in IoT enterprise spending (IoT Analytics will publish the 2022 IoT spending actuals shortly). The public relevance of the term "IoT," which had been on the decline since October 2018, climbed back up by more than 30% to reach its all-time high levels in Q1 2022. Throughout 2022, we monitored significant developments regarding IoT technology. In the aftermath of the global pandemic and war in Ukraine, reports of congested ports, suppliers halting production, or critical cargo going missing became normal news in 2022.

In many parts of Asia, seasonal torrential rains bring with them floods that damage property and livelihood of citizens. Whereas in the past, city administrations, citizens and businesses can do almost nothing but ride out the unwelcoming waves of flood water and the potential diseases these carry, technologies like the Internet of Things (IoT), machine learning (ML) and artificial intelligence (AI) may provide respite for more forward-looking leaders. This is the case of the DKI Jakarta Provincial Government's Flood Control System in the Jakarta Smart City application. Developed by Jakarta Smart City in collaboration with the Jakarta Water Resource Service (DSDA) to optimise flood risk management in Jakarta, the project involved the use of IoT, AI and ML as part of an early warning system against the risk of floods in the city. As more organisations deploy IoT in commercial and industrial environments, the amount of data that is derived from these devices and sensors may prove important in improving quality, operational efficiency, and in the case of Jakarta – saving lives and property from natural disasters.

Similarly, nearly two-thirds (65%) are in various stages of implementing their IoT strategy. Although the pandemic, looming recession, inflation, and global supply chain issues have been prevalent topics in the last year(s), manufacturers are determined to fast-track their digital transformation projects in the next three years. With nearly three-quarters of manufacturers currently implementing a smart factory strategy, we were curious to find out what manufacturing KPIs are most important to measure the success of this transformation. We prompted the decision-makers with 27 different manufacturing KPIs and asked how important each one is for their smart factory project. This is just one of many analyses of the 59-page IoT Signals Report – Manufacturing Spotlight (August 2022), published by Microsoft and Intel, with research conducted by IoT Analytics.

Hannover Messe (or Hannover Fair), the #1 global industrial tradeshow, was back in action earlier this month. The event that took place from 30 May–02 June 2022, in Hannover, Germany, showcased once again the latest developments and industrial technology trends. Despite a much smaller crowd (75,000 visitors--roughly 40% of pre-pandemic levels), the fairgrounds were buzzing and filled with senior executives from many of the leading industrial hardware, software, and service providers. The conference remains one of those rare fairs where you randomly walk into senior executives, like a Head of Engineering for a major industrial conglomerate, and not only into the pre-sales representatives giving you the usual pitch. "In the face of disrupted supply chains, rising energy prices, inflation, and climate change, it was all the more important to meet face-to-face again in the exhibition halls after two years marked by a pandemic, to take in the latest technology trends and get a window to the future."

The AI adoption rate in industrial settings has increased from 19% to 31% in slightly more than two years, according to data from the recently released 252-page Industrial AI and AIoT Market Report 2021–2026. On top of the 31% of respondents that have fully or partially rolled out AI technology in their operations, an additional 39% are currently testing or piloting the technology. Increased AI adoption can be witnessed across the board but is especially strong in the energy vertical and in process industries, such as oil and gas or chemicals. The combination of high-value assets, large volumes of operational data, and processes that rely on hundreds of parameters contributes to the strong adoption in these industries. Common industrial AI applications include maintenance (e.g., predictive maintenance [PdM]), predictive quality control, the use of machine vision for fault detection, AI-optimized inventory management, and AI-based production planning and optimization.

The process of steelmaking has been the same for thousands of years, using the traditional, coal-fired blast furnace. But SSAB is bringing steelmaking into a sustainable future. Using electricity, hydrogen and new digital tools, the highly specialized global steel manufacturer plans to produce fossil-free steel products in 2026. By 2045, SSAB's vision is to create a complete, fossil-free value chain from customers to end-users. To achieve this goal, almost all SSAB's processes need to have a digital component – and many of the decisions made in daily production need to be driven by analytics.

The internet of things (IoT) is increasingly becoming a key component of many companies' data-driven transformation strategies. Indeed, organizations that have embraced IoT are already seeing benefits such as improved operational processes, better inventory management, and enhanced equipment maintenance -- to name a few. But a successful IoT strategy is more than just connecting a bunch of devices and sensors to the internet and gathering data from these "things." IT must establish the ability to effectively analyze the vast amounts of data IoT creates in order to make sense of it and gain real business insights. That's why an analytics strategy for IoT should be a top priority for any company looking to get the most out of all the connectivity.

Intelligent connectivity is a concept that foresees the combination of 5G, the Internet of Things and artificial intelligence as a means to accelerate technological development and enable new disruptive digital services. In the intelligent connectivity vision, the digital information collected by the machines, devices and sensors making up the Internet of Things is analysed and contextualised by AI technologies and presented to users in a more meaningful and useful way. This would both improve decision-making and allow delivery of personalised experiences to the users, resulting in a richer and more fulfilling interaction between people and the environment surrounding them. As artificial intelligence becomes increasingly sophisticated thanks to advances in computing power, the education of data scientists and the availability of machine learning tools for creating advanced algorithms, the Internet of Things is getting closer to becoming a mainstream phenomenon. The ultra-fast and ultra-low latency connectivity provided by 5G networks, combined with the huge amount of data collected by the Internet of Things and the contextualisation and decision-making capabilities of artificial intelligence technologies will enable new transformational capabilities in virtually every industry sector, potentially changing our society and the way we live and work.

In 2019, enterprise demands rose for real-time and near real-time analytics, and data continued to expand its role in everyday business operations and decision-making. Enterprises will continue to build on these trends in 2020, and that will drive analytics vendors to add new capabilities and expand their offerings. Here are eight key trends for analytics in 2020. In-memory costs are decreasing, and this will drive more analytics to real-time environments. The demand for real-time or near real-time analytics will require fast CPUs and in-memory processing.

While conducting research for the recently released Industry 4.0 and Smart Manufacturing Market Report, IoT Analytics identified 300 leading Industry 4.0 companies that supply cutting edge products and services that are driving the fourth industrial revolution. The leading Industry 4.0 companies were selected based on a number of criteria (case studies, product offerings, estimated market share, etc.) and were categorized based on what type of Industry 4.0 product or service they supplied. Building on its long history of supporting industrial automation companies, Microsoft has emerged as the hosting partner of choice for many Industry 4.0 companies. Both end users (manufacturing facilities) and suppliers (OEMs, industrial automation companies, etc.) have partnered with Microsoft to develop and run mission-critical on-premise SCADA and MES applications for decades. Microsoft's deep domain knowledge and technical capabilities (especially with respect to hybrid cloud solutions) have helped it become a leading provider of hosting services for major manufacturing end users and suppliers such as Siemens, PTC, GE, and Emerson.