Nowadays, one of the technology markets with more growing potential in the coming years is without doubt the Internet of Things (IoT) market. Many experts affirm that the global IoT market must experiment a strong growth during the forecast period 2020 to 2028. Xymbot tech post will focus on current market trends, leading players, supply chain trends, technological innovations, key developments, and future strategies.
The Internet of Things can now be considered a mature technology with a multitude of options both in terms of connectivity, hardware and use cases already available on the market. 2019 was an exceptional year for the IoT, which experienced higher than expected growth in terms of connected devices. In fact, according to IoT Analytics, active IoT devices reached 9.5 billion in 2019 much more than the 8.3 billion previously estimated, gathering the top 5 trends identified by experts and observing the major venture capital operations that have involved the IoT sector during the last year as: global connectivity, security, software as a service (SaaS), edge computing and data analytics .
On the other hand, a McKinsey report predicts that, by 2025, the overall economic impact of the IoT could reach $11.1 trillion, surpassing sectors such as Mobile Internet, Process Automation or Cloud technology.
The same report highlights that factories and other process-driven production environments such as hospitals and farms, are likely to reap the greatest benefits from the adoption of IoT systems as much as $3.7 trillion by 2025. In this type of venue, which includes any standardized production environment, the value will come from improvements in energy efficiency, labor productivity, equipment maintenance, inventory optimization, and worker health and safety.
As it has been described in previous posts, 5G is called to play a key role in the smart-factory or Industry 4.0 roadmap (read more). it’s a smart bet that this year will see the full emergence of digital manufacturing, powered in part by the improved connectivity the new standard offers. In such manufacturing, computer platforms control a range of systems functioning at high levels of integration. Operational data feeds from sensors into the platforms’ AI-driven analytical engines, letting the platforms refine in real time how those complementary systems work. The results are levels of efficiency and productivity of which pre-IoT manufacturing could only dream. Another result of the Industrial IoT (IIoT) improvement in the smart-manufacturing processes is the hyper-customization of products. Now, by customization in mass production we don’t mean what we did a few years ago. In this direction, 3D scanning and modelling tech support this customization capability.
Into the IIoT applications, predictive maintenance is one of the most promising field to be transformed during the digitalization of the industrial processes. Sensor-equipped industrial equipment generates data that AI apps can use to monitor status and even predict failure a state of affairs that’s making obsolete the reactive, planned, and proactive maintenance regimes of the past. Predictive maintenance apps minimize the unplanned equipment downtime, maintenance cost and extend the components and assets remaining useful life, optimizing the maintenance scheduling, spare part & stock management and expert team allocation. Managers could anticipate exactly when that gasket will blow, and make sure that everything is setting on time to avoid or minimize the impact of a predicted failure, saving production time, resources and money .
In order to success on the increase the anticipation, prediction and cognitive capabilities of smart-devices in our daily activities, distributed IoT analytics and data are finding applications in IoT networks. This method lets systems trigger alerts or action sans transferring volumes of data to network cores. This results in improved performance as networks operate at low latency. The integration of data streams with machine learning and AI engines to create smart-nodes as Empowered Edge (read more) are the new trend in the IoT-based solutions. Integrated analytics are now being embedded into solutions as providers seek to speed up data analysis. Such analytics are directly fed into machine learning apps. This design supports IoT devices, processes and infrastructure adaptation and optimization. IoT data will be sold as a commodity, which will be targeted mostly at appliance manufacturers .
As probably you already know, IoT applications have been used across a variety of sectors impacting our daily life, including manufacture, automotive, cities, home or healthcare, among others (read more), being a challenge to cover all of them in one single post. Nevertheless, we have selected the IoT-based impact on climate change to conclude our weekly publication, as a clear example of how social innovation actions should be addressed by researchers and companies in order to build a smart and sustainable society of the future.
Alex Gluhak, head of technology at Digital Catapult, said that “IoT is the digital skin of our planet”. A skin that consists of sensors, devices, and software focus on reducing the carbon footprint of various processes such as: reduce waste and make better use of natural resources. The goal is to combat climate change and avoid natural disasters. But there is also one other issue, not directly related to climate but equally important. Using IoT early warning systems, experts and authorities can save lives with timely evacuations from areas prone to rockslides, e.g., the Norwegian fjords, where giant rocks falling into the water can cause massive tsunamis .
In future posts, we will be continue writing about technology and business trends for enterprises. Furthermore, we recommend consulting the following literature to continue your digital transformation journey:
- Designed for Digital: How to Architect Your Business for Sustained Success, MIT review
- The Future Is Faster Than You Think: How Converging Technologies Are Transforming Business, Industries, and Our Lives, by Simon & Schuster
- Artificial Intelligence: The Insights You Need, by Harvard Business Review
- The Year in Tech, 2021: The Insights You Need, by Harvard Business Review
- The Deep Learning Revolution, by MIT Press
- Competing in the Age of AI, by Harvard Review Press
The objective of this blog is to provide a personal vision of how digital transformation trends will be impacting in our daily activities, businesses and lifestyle.
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