Enhancing OSH Management Processes through the Use of Smart Personal Protective Equipment, Wearables and Internet of Things Technologies

Daniel Podgorski

Industry 4.0 and ICT-Based Management of OSH

The global economy is driven by global competition and the need to rapidly adapt production processes to quickly changing market needs and requirements. These requirements can only be achieved through radical advances in manufacturing technologies, often referred to as the digital transformation of industry, as they aim at a profound integration of digital technologies and business processes leading to new business models.

Meeting the challenges of the digital transformation lies at the heart of the so- called fourth industrial revolution, which is often labelled as Industry 4.0, and is characterised first of all by the widespread automation of industrial processes, including the extensive use of industrial and collaborative robots, additive manufacturing technologies, the concepts of industrial Internet of Things (IIoT), cyberphysical systems (CPS), cloud and edge computing, as well as the use of advanced data analytics methods, including machine learning and the dimension of big data.

The term Industry 4.0 was used for the first time in 2011, to describe a joint initiative of representatives of business, government and academia within the “High- Tech Strategy 2020 for Germany” concerning the promotion of computerisation of manufacturing and applications of digital technologies in industrial sector in order to strengthen the competitiveness of German industry (Kagermann et al. 2011). This term is now widely used worldwide and has been successfully adapted to shape and promote new industrial policies in many countries.

The central paradigm of Industry 4.0 is the introduction of the idea of the smart factory, a factory that will be equipped with the context-awareness functions and may assist people and machines in a holistic way in execution of their tasks. Such a factory is to provide the possibility of product customisation considering individual and changing customer needs, as well as making possible rapid adaptation to market changes and emergency situations, ensure efficiency of the use of resources and energy, building new models of co-operation with partners and extending the production process to suppliers and customers.

With the development of the above-mentioned concepts and digital production technologies, there have also been attempts to develop and apply ICT applications in the field of OSH, in order to ensure an adequate level of safety and health in workplaces functioning within the processes of smart manufacturing. This includes, in particular, the use of new sensor technologies, which offer opportunities to improve the safety and health of workers by real-time monitoring of various harmful and noxious parameters of the working environment. In addition, the use of new materials, sensors and telecommunications technologies in combination with cloud computing and big data analytics methods makes possible the introduction of other functions that are key to the effective management of OSH, such as the identification of hazards and reducing the associated risks in real time, detection of unsafe workers’ behaviours, automatic incident detection and recording, monitoring of the effectiveness of individual OSH management processes, identification of workers’ needs w'ith regard to training and skills improvement in specific OSH fields, and many others.

Against that background, the purpose of this chapter is to provide an overview of the digital transformation issues to demonstrate the potential of the newest technologies to manage safety and health at work, which is especially important given the global trends in the development of intelligent manufacturing systems. In particular, this chapter will review the roles of smart personal protective equipment (smart PPE) and other smart wearable devices for workplace applications, with a particular emphasis on the usefulness thereof in the context of IT-empowered OSH risk management. These issues will be complemented by an analysis of the potential application of big data analytics for OSH management, as well as by discussing the inter-related aspects of privacy, personal data protection and cyber-security, which are becoming more and more important, and to some extent a hindrance to the more widespread dissemination and application of otherwise useful digital technologies in the workplace.

The development of smart PPE technologies and wearable devices for use in the working environment

Definition and Roles of Personal Protective Equipment in Protecting Workers against Hazards and Risks

Personal protective equipment (PPE) is usually defined as “equipment designed and manufactured to be worn or held by a person for protection against one or more risks to that person's health or safety” (European Union 2016a). PPE items are often divided into groups and types on the basis of parts of the human body to be protected and with regards to the risks they provide protection against. The commonly used PPE typologies divides these products into the following main groups:

  • • protective clothing (including PPE signalling the user’s presence visually, and lifejackets);
  • • protection against falls from height (full body harness, waist belts, fall arresting devices, anchor devices, etc.);
  • • hearing protection (earmuffs and earplugs);
  • • eye and face protection (goggles, safety glasses, face shields);
  • • respiratory protection (filtering devices, insulating devices, breathing equipment);
  • • hand and arm protection (safety gloves, elbow pads);
  • • foot and leg protection (footwear, instep protectors, kneepads);
  • • skin protection (barrier creams).

In accordance with the classical hierarchy of occupational risk controls PPE is considered as a last resort in risk reduction, because it should be taken into account only when higher level types of controls are not feasible or effective to limit the risk to an acceptable level. Despite the fact that this hierarchy does not arise from a specific research base, it has been widely accepted by OSH professionals and presented in a similar way in many national and international standards, guidelines and legal requirements concerning OSH management (Manuele 2005). For example, international standard ISO 45001:2018 (ISO 2018), which defines specifications for OSH management systems, refers to the hierarchy of risk controls (clause 8.1.2) in the following way:

The organisation shall establish, implement and maintain a process(es) for the elimina tion of hazards and reduction of OH&S risks using the following hierarchy of controls:

  • a) eliminate the hazard;
  • b) substitute with less hazardous processes, operations, materials or equipment:
  • c) use engineering controls and reorganisation of work;
  • d) use administrative controls, including training;
  • e) use adequate personal protective equipment.

Despite the convincing logic behind the above-mentioned hierarchy, as well as several decades of its application in practice, the use of PPE is still one of the most effective methods of reducing OSH risks in many industrial sectors and workplaces. This is particularly true for workplaces with complex and harsh environmental conditions exposing workers to a wide range of life and health risks at the same time, and for workplaces where risk factors change dynamically in an unforeseen way, thus hindering or preventing the use of rationally designed protective measures representing the higher levels of risk controls hierarchy.

Smart PPE-Enabling Technologies

The dynamic development of technologies in such domains as materials engineering, electronics, computer science, and wireless telecommunication, which have taken place over the last few decades is characterised by the striving for miniaturisation of devices, the increasing mobility of computing systems, as well as the development of distributed systems constituting a set of independent smart objects and technical devices combined into one logically coherent whole (the Internet of Things [IoT]). At the same time, there is better and better mastering of sensor technologies that enable one to sense (i.e. to detect) some physical, chemical or spatial characteristics of real- world objects and environments. As a result, a number of advanced concepts and enabling technologies are available, which offer practically innumerable possibilities of creating and improving various smart PPE solutions.

Enabling technologies belonging to the field of functional and smart textile materials deserve particular attention, as this field covers a wide range of different material technologies that make possible specific functions obtained by means of material composition, construction and/or finishing, and which are based on the use of various physical and chemical phenomena. Taking these phenomena as the basis for the typology, as proposed in the CEN/TR 16298 technical report (CEN 2011), the types of functional textile materials include textile materials that are electrically conductive, thermally conductive, thermally radiative (emissive), optically conductive, fluorescent, and phosphorescent, as well as textile materials which release specific substances. Smart textile material can be defined as a functional textile material which interacts actively with its environment, i.e. responds or adapts to changes in the environment.

In addition to material technologies, the development of smart PPE has also been driven by significant achievements in other contemporary engineering disciplines, such as:

  • • health monitoring micro- and nano-sensors integrated with textiles;
  • • flexible, stretchable and conformal electronics (elastronics);
  • • MEMS (micro-electro-mechanical systems) and LOCs (lab-on-a-chip);
  • • ultra-low power electronics and energy harvesting technologies (thermoelectric, piezoelectric, photovoltaic, electrodynamic, etc.);
  • • wireless telecommunication technologies and protocols, such as RFID, iBeacons, Wi-Fi, NFC, Bluetooth, BLE (Bluetooth Low Energy), ZigBee, Z-Wave, UWB, etc.;
  • • augmented- and mixed-reality technologies;
  • • cloud computing[1] and edge computing1 applications; and
  • • machine learning algorithms and big data analytics.

In particular, the last two of the areas mentioned above deserve greater attention, as the development of applications based on cloud and edge computing technology has made possible a significant increase in the amount of data that can be collected and processed in smart PPE systems in real time. Whereas, the application of machine learning algorithms, including the use of methodologies making possible the processing of massive amounts of data (i.e. big data), enable one to obtain actionable insights, which can very useful for the introduction of advanced functions in the area of OSH. These issues will be explained and illustrated in more detail in the other sections of this chapter.

The general fundamental feature of smart textile material, which is the intrinsic ability for automatic reaction to changes in the surrounding environment, can be used to define the entire category of smart PPE systems that demonstrate the same feature. Taking this approach into account the following definition was proposed:

A smart personal protective system (SPPS) is an assembly of devices or elements that is designed to be worn or held by a person for protection against one or more health and safety hazards, and that reacts automatically, either to changes in its environment or to an external signal. (Marchal and Baudoin 2018)

  • [1] Cloud computing is the on-demand availability of computer system resources, especially data storageand computing power, without direct active management by the user. The term is generally used todescribe data centres available to many users over the Internet (Wikipedia: https://en.wikipedia.org/wiki/Cloud_computing, accessed August 6,2019). f Edge computing is a distributed computing paradigm which brings computation and data storagecloser to the location where it is needed, to improve response times and save bandwidth (Wikipedia:https://en.wikipedia.org/wiki/Distributed_computing, accessed August 6,2019).
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