Wearable Sensors

Trend Overview

Impact:

Limited

Adoption:

< 5 Years

Focus Areas:

Automation & Efficiency Health, Safety & Future of Work Physical & Digital Security

Trend Clusters:

Bionic Enhancements Internet of Things

Sectors:

The trend of Wearable Sensors encompasses sensors that are worn on, close to or even in the human body with the purpose of tracking body movement or vital functions. Depending on the type of information to be captured, different sensors like gyroscopes and accelerometers are integrated into wearable products, from badges and wristbands to smartglasses and clothing.

For many individuals, it has become hard to imagine doing sports without a fitness tracker or smartwatch to track performance via built-in sensors. The technology holds a lot of potential especially within the healthcare sector where wearable sensors could, for example, pave the way for improved remote diagnostics being able to capture physiological data and transmit it via low-power wide-area-network (LPWAN) technology.

Wearable sensors are continuously developing to become smaller in size. This opens new possibilities; for example, they can be worn as part of a person’s clothing or even integrated in the human body. Biolinq, a California-based startup, for instance, recently raised US$ 58 million for its development of the world’s smallest biosensor worn just beneath the skin to measure a person’s glucose levels.

Many companies, including those in the logistics industry, have started to recognize the value of extracting data from wearable sensors for industrial applications, particularly in the realm of employee health and safety. As such, many logistics organizations have begun procuring various forms of smart wearable devices and setting up wireless communication infrastructure in their facilities, like Bluetooth Low Energy (BLE), Wi-Fi, or – if a real-time location system (RTLS) is needed – even ultra-wideband (UWB).

While the impact of this trend on the logistics industry is expected to be moderately low, wearable sensors represent one of the building blocks towards making better, data-based decisions. Already today wearable sensors are leveraged within logistics to provide valuable insights, making working environments safer and more efficient. It is important to note that many applications involving wearable sensors are already technically feasible. However, anonymity and data protection are very important and must be considered, which can often be a limiting factor.

Wearable sensors

Source: Kong, Xiang (2019): Industrial wearable system: the human-centric empowering technology in industry 4.0

Relevance to the Future of Logistics

Process Intelligence

Optimizing operational processes is essential, especially for those where visibility is typically lacking. It is therefore very useful for companies to deploy wearable sensors capable of automating the collection of data and insights during logistics operations.

For example DHL Supply Chain is already using Motion-Mining®, a general data protection regulation (GDPR)-compliant solution developed by a German startup, that leverages data collected from purpose-built wearable devices during a temporary installation to identify process waste and improvement potential. The automation of data collection leads to larger, more detailed data sets which are free from observation biases. Data can be automatically analyzed using algorithms to generate detailed insights and enable data-based decision making.

As more and more wearable devices such as smartglasses and wearable scanners get implemented in logistics operations, new possibilities open up to generate insights on a more permanent, continuous basis leveraging the built-in sensors of these devices. For example ProGlove, a startup known for its wearable scanners, offers a platform called ProGlove Insights alongside its products to provide useful process insights that boost visibility.

Next use case

Ergonomic Health

Ergonomic hazards in the workplace are one of the main causes of musculoskeletal disorders (MSDs) which are the most common work-related health issue in the European Union (EU). This results in high costs for the organization as workers require sick leave and may have to retire early. Wearable sensors can be used to lower the MSD risk in two ways – either by using data-driven insights to evaluate and mitigate the ergonomic risk of a process or workplace or by training employees to adjust their actions to more ergonomically friendly movements.

Soter Analytics and Kinetic are two examples of providers that offer wearable sensors for ergonomic training purposes. The idea is to give real-time feedback to a user by vibrating or beeping when a hazardous movement such as bending and twisting is performed. These solutions create awareness and trigger a change in behavior over time, reducing the amount of hazardous movements performed.

Also, vital body data captured through wearable sensors has various applications such as fatigue detection and alerting when certain stress levels are reached. The sensitivity of this type of data calls for strict anonymization in order to obtain user acceptance.

Previous use case Next use case

Location Identification

The ability to track employee location opens an array of application fields. There are various health and safety (H&S)-related use cases such as the localization of a worker in the event of a person-down alert. Also, to prevent accidents between pedestrians and forklifts inside an operational facility, a collision warning can be issued both to the worker and the driver so they can take preventative action – a use case that requires high accuracy and data transmission in real time.

Another interesting use case is leveraging wearable sensors for automated reporting. The collection of data about an operational employee’s time spent in certain physical areas of a facility that serve multiple customers can automate the capturing of work hours attributable to each customer; this also allows for a fully automated billing process. In addition, wearable sensors can automate access control within a facility, restricting access to certain areas or to the use of particular vehicles and tools based on the individual’s experience or training level.

Typically the trade-off between cost and the required accuracy as well as speed of data transmission dictates which type of technology is used for localization. While ultra-wideband-based solutions provide high-accuracy tracking in real time, the high cost of the required devices and infrastructure makes it unrealistic to scale. Where BLE can offer sufficient accuracy, it is preferred due to the lower cost of implementation. Sonitor for example, a Norwegian startup, is leveraging BLE or ultrasound technology to make use of real-time indoor localization for automated labor reporting, geo-fencing, or indoor navigation purposes.

Previous use case

Challenges

Wearable sensors raise data protection concerns about sharing personal and performance information with the employer; to succeed, solution providers must ensure GDPR-compliant anonymization of data.

As more wearable sensor use cases arrive, there is a risk of overloading the employee with wearables and sensors; where possible, companies should avoid introducing new hardware for every new application.

Infrastructure requirements are highly dependent on the level of precision and the frequency of data sharing required; especially for RTLS use cases, infrastructure investment is significant and may not provide sufficient return on investment for a single application.

Wearable sensors raise data protection concerns about sharing personal and performance information with the employer; to succeed, solution providers must ensure GDPR-compliant anonymization of data.

Challenge 1 Challenge 2 Challenge 3

Outlook

As more wearable devices such as smartglasses for vision picking and wearable scanners are introduced into logistics operations, here at DHL we are already starting to see decisions to leverage data from built-in sensors rather than introduce new purpose-built devices for each and every use case.

For use cases requiring accurate localization of employees, we still see cost as a limiting factor to scalability. In future, however, we anticipate a democratization of devices and support infrastructure, bringing down the cost per use case, with generic gateways lowering the entry barrier for these kinds of applications.

We also see technological advancements – like the miniaturization of electronic components and flexible printed circuit boards (PCBs) and increases in battery life – accelerating the subtle integration of sensors into clothing. Relatedly, but in another direction and further into the future, we anticipate the development and possible movement of sensors from on the human body to inside the body as multifunctional implants.

This trend should be PASSIVELY monitored,with implementations available for many use cases today.