Category: IIoT

Bluetooth in the IoT Ecosystem

The great new paper titled Evolution of Bluetooth Technology: BLE in the IoT Ecosystem provides a comprehensive review of Bluetooth Low Energy (BLE), tracing its development from its origins to its role in the modern Internet of Things (IoT). The authors outline the historical evolution of Bluetooth, starting with its initial release in the late 1990s through to the latest version, Bluetooth 6.0, introduced in 2024.

BLE, introduced in Bluetooth 4.0 in 2010, was designed as a low-power alternative to Bluetooth Classic, making it ideal for IoT applications where energy efficiency is critical. The paper discusses BLE’s technical characteristics, such as its reduced power consumption, moderate data rates, mesh networking support, and robust security features and highlights the differences from Bluetooth Classic.

The review details the progression of BLE through its successive versions, each introducing improvements in range, throughput, latency, and security. It also explores the integration of BLE in various IoT contexts, including smart homes, healthcare, automotive, retail, industrial automation, and smart cities. Several case studies are used to illustrate real-world BLE implementations, demonstrating its utility across multiple sectors.

The paper considers BLE’s alignment with the United Nations’ Sustainable Development Goals (SDGs), particularly in promoting energy efficiency, sustainable urban development, and climate action. BLE’s role in enabling sustainable technologies, such as solar-powered IoT devices and low-power smart infrastructure, is also discussed.

Finally, the article reviews current technical challenges, such as power management, interference, scalability and security. It proposes potential solutions and anticipates future directions involving BLE’s integration with artificial intelligence, enhanced privacy protocols and expanded functionality in next-generation IoT ecosystems.

Matching Industrial Assets and Their Operators

Recent research looks into a new method for linking industrial assets, like power tools, with their operators using low-power Internet of Things (IoT) devices based on Bluetooth Low Energy (BLE). Despite the wide adoption of asset-tracking technologies, there’s still no widely used solution for dynamically identifying which worker is using which tool. This is important for improving safety, maintenance, and asset utilisation, especially in complex and fast-paced environments like construction sites.

The proposed system includes wearable devices for workers and beacons tags attached to tools. These beacons broadcast data about their usage status, which is picked up by the wearables. The system uses signal strength (RSSI) to estimate the proximity between workers and tools. Since RSSI data is noisy and imprecise, an Extended Kalman Filter (EKF) is employed to improve distance estimation accuracy. A cloud-based algorithm then analyses this data to identify the most probable asset-user matches.

The researchers implemented and tested this system using prototypes in both indoor and outdoor construction settings. The system achieved a median distance estimation error of 0.49 metres and up to 98.6% accuracy in matching tools to their users. The devices were optimised for low energy consumption: wearable devices could run for nearly a month on a single charge, and tags could last for years on small batteries.

The study concludes that the proposed system is a viable and scalable solution for enhancing digitalisation in industrial environments, particularly construction.

Bluetooth Technology is Driving IIoT

Bluetooth technology is playing a transformative role in the Industrial Internet of Things (IIoT), facilitating the digitisation and networking of manufacturing operations to address economic, supply chain and regulatory challenges. This wireless technology enables comprehensive data collection, monitoring, and analysis across interconnected devices, which are critical to the automation and efficiency goals of Industry 4.0.

Bluetooth Low Energy (LE) technology has growing importance in industrial settings. According to the 2023 Wireless Connectivity Market Analysis by Techno Systems Research and ABI Research, the market for Bluetooth-enabled industrial devices is projected to grow significantly, from 143 million annual unit shipments in 2023 to over 611 million by 2028, with a compound annual growth rate (CAGR) of 34%. Real-time location systems (RTLS) and asset tracking represent the largest market opportunity due to the availability of low-cost Bluetooth LE tags offering high-accuracy location services.

The second-largest growth area is commercial building automation, which is forecast to expand rapidly, from 8.5 million unit shipments in 2022 to over 135 million by 2028. Other notable markets include Bluetooth LE condition monitoring and predictive maintenance, expected to reach 7 million and nearly 10 million annual unit shipments respectively by 2028.

Robotics is another significant area of opportunity, where Bluetooth LE is enabling autonomous navigation and robot-to-robot communication. Mobile robots, in particular, stand out as they can relay crucial operational data such as position, load, and battery levels, while also allowing for dynamic updates to tasks and routes via Bluetooth-connected devices.

Key advantages of Bluetooth technology in industrial applications include its low power consumption, resilience to interference, robustness, and integration with existing mobile, computing, and IoT infrastructure. Its ability to provide real-time insights into factory operations through extensive data collection, combined with advanced wireless System-on-Chip (SoC) technologies, facilitates improved decision-making and operational adaptability.

This technological advancement extends beyond operations, linking the design and manufacturing processes. By connecting tools like CAD directly to machine tools, Bluetooth enables seamless communication to streamline production, reduce bottlenecks, and enhance product design for simpler manufacturing. These capabilities yield higher productivity, reduced product failures, cost savings, and environmental benefits, revolutionising not only how products are made but also how factories are managed and adapted.

Digital Manufacturing on a Shoestring

In a previous post we asked ‘What is Productivity?’ and shared how the first wave of IT productivity related to cloud computing, customer relationship management (CRM) systems and enterprise resource planning (ERP) was only taken up by the top 5% frontier companies.

We explained how IoT, 4IR and AI machine learning will improve productivity but again, likely only for frontier companies. The difference this time is that the newer technologies will have more far reaching consequences. The frontier companies will further extend their reach over the laggards. The majority of the 5% are large companies with large budgets who are able to engage consultances such as IBM, Deloitte, Atos, PwC, WiPro, Accenture and KPMG. But what of the small to medium enterprises (SMEs)? Can they compete?

In most countries, a large proportion of companies are small to medium size. For example, in the UK, the Office for National Statistics says 98.6% of manufacturers are (SMEs). These organisations are more price sensitive and usually don’t have the luxury of significant financial resources for engaging the top consultancies and implementing their expensive solutions. Small and medium sized organisations have previously found it difficult to digitise due to the lack of availability of reasonably priced solutions.

However, solutions doesn’t have to be expensive. Low cost sensors such as Bluetoooth beacons, motion cameras, consumer AR can be combined with affordable cloud services to create solutions on a ‘shoestring’ budget. This is the aim of the University of Cambridge and University of Nottingham’s ‘Digital Manufacturing on a Shoestring’ initiative. The Institute for Manufacturing (IfM) is helping manufacturers benefit from digitalisation without excessive cost and risk. View the project’s latest news.

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IoT Projects with Bluetooth Low Energy

Our article on Beacon Proximity and Sensing for the Internet of Things (IoT) provides short summary how to use Bluetooth for IoT.

If you need a more rigorous description take a look at the book IoT Projects with Bluetooth Low Energy. It covers the fundamental aspects of Bluetooth Low Energy scanning, services, and characteristics. It goes on to describe examples of how to monitor health data, perform indoor navigation and use the Raspberry Pi for Bluetooth solutions. The book’s code is also available on GitHub.

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Bluetooth Mesh for Industrial IoT (IIoT)

There’s an informative video presentation on the Bluetooth SIG web site on Simplifying Multi-Vendor Mesh and Sensor Networks. It provides an introduction to Bluetooth mesh and explains the ways in which it can provide for Industrial IoT (IIoT).

To add to this, Bluetooth Mesh is suitable for use on the factory floor where the environment can be electrically noisy. Standard Bluetooth Mesh uses advertising on several channels rather than (GATT) connections so as to provide for more reliable communication in environments with wireless interference.

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Bluetooth Mesh and IIoT in Factories and Warehouses

Dialog Semiconductor, the manufacturer of the SoC chip in some beacons, has an informative article on How Bluetooth Mesh and IIoT are Reimagining Factories and Warehouses. It explains how the recent introduction of Bluetooth mesh has created new opportunities in the Industrial Internet of Things (IIoT).

“The manufacturing industry is absolutely ripe for potential with Bluetooth mesh”

IDC

“Industrial sensors and smart buildings among other use cases, are expected to outpace the overall Bluetooth LE market by 3X through 2022”

Research and Markets

The article mentions preventive maintenance, air quality sensing, asset tracking, robot control systems and traditional air conditioning as possible applications for Bluetooth Mesh. However, a key insight is that once a mesh network is in place it can be used for applications beyond those originally envisaged.

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IoT Priority and Asset Tracking

Gartner has a new report Hype Cycle for the Internet of Things 2019, in which they say:

“The Priority Matrix shows that many IoT technologies are 5 years from mainstream adoption. However only one innovation profile will reach maturity in 2 years, indoor location for assets.

So why is ‘indoor location for assets’ more likely to achieve mainstream adoption sooner than other technologies? It’s because there are clear benefits for most companies and off-the-shelf software such as our BeaconRTLS™ is already available.

Our work with companies shows they are nevertheless cautious. Companies are taking time to understand the competing asset tracking technologies and are performing, sometimes lengthy, trials to determine how new systems will integrate with existing systems. They are considering the implications of SAAS vs on-premise solutions, the availability of second-sourced beacon hardware and the compromises of accuracy vs system complexity and cost.

Why Bluetooth is Perfect for the Industrial IoT (IIoT)

U-Blox has a useful article on Seven reasons why Bluetooth is perfect for the Industrial IoT, echoing some of our observations on Bluetooth LE on the Factory Floor. The article explains why Industrial Internet of Things (IIoT) systems and networks should consider Bluetooth as the communications infrastructure.

As U-Blox mentions, there’s predicted to be 5.2 billion Bluetooth device shipments by 2022. This data is from the latest Bluetooth SIG/ABI research:

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How to Start Industry 4.0 and Digital Transformation

There’s lots said about the advantages of Industry 4.0 or Digital Transformation and the associated new technologies but it’s a lot harder to apply this to the context of a business that has legacy equipment and no real way of knowing where to start.

Our previous article on productivity explained how, historically, digital transformation has been only been implemented in the top 5% ‘frontier’ companies. These have tended to be very large companies with large R&D budgets that have enabled customised digital solutions. More recently, the availability of less expensive sensors and software components have extended opportunities to the SME companies. These companies are already realising gains in profitability, customer experience and operational efficiency. Unlike previous technologies, such as CRM, the newer technologies such as IoT and AI are more transformative. Companies that don’t update their processes risk being outranked by their competition with a greater possibility of going out of business. But where do you start?

The place to start is not technology but instead something you and your colleagues fortunately have lots of experience of : Your company. Take an honest look at your processes and work out the key problems that, if solved, would achieve the greatest gains. You might have ignored problems or inefficiencies for years or decades because they were thought to be insolvable. Technology might now be able to solve some of these problems. So what kind of problems? Think in terms of bottlenecks, costly workrounds, human effort-limited tasks, stoppages, downtimes, process delays, under-used equipment and even under-used people. Can you measure these things and react? Can you predict they are about to happen? This is where sensing comes in.

The next stage is connectivity. You will almost certainly need to upgrade or expand your WiFi and/or Ethernet network. It can be impractical to put sensors on everything and everyone and connect everything by WiFi/Ethernet. Instead, consider Bluetooth LE and sensor beacons to provide a low cost, low power solution for the last 50 to 100m. Bluetooth mesh can provide site-wide connectivity.

Initially implement a few key improvements that offer good payback for the effort (ROI). The improvements in efficiency, productivity, reduced costs and even customer experience should be enough to convince stakeholders to expand and better plan the digital transformation. This involves replacement of inefficient equipment and inefficient processes using, for example, robotics and 3D printing. It also involves analysing higher order information combined from multiple sources and using more advanced techniques such as AI machine learning to recognise and detect patterns to detect, classify and predict. This solves problem complexity beyond that able to be solved by the human mind or algorithmic program created by a programmer.

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