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Unlock the full potential of your information management solution
Turn support into your strategic advantage
Extend IT teams with certified OpenText application experts
Discover training options to help users of all skill levels effectively adopt and use OpenText products
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To reduce injury rates for workers, cut healthcare costs and boost industrial productivity, LWT3 is using OpenText™ Vertica to power an advanced biomechanical analytics solution
To help reduce occupational diseases, LWT3 wanted a flexible, high-performance platform for analyzing enormous bio-mechanical data sets.
LWT3 designs, manufactures, and tests IoT devices and wearables, powered by physiological sensors that provide data to help discover the root causes of human bio-mechanical stresses. The company gathers the data in real-time, and completes its analysis using big data and machine learning platforms, all protected by blockchain-based data security engines.
VerticaPy brings many functions available in the Anaconda stack to Vertica (now OpenText), making it easy to use existing Python code and develop additional functionalities, essential for our plans to expand WINGS into other sectors.
In a specific project, the company is working with industry partners to address the challenges of Musculoskeletal Disorders (MSD). According to the European Agency for Safety and Health at Work, more than half of the 159 million workers in Europe suffer from MSD. And of the 61 million people working in manufacturing, construction, and logistics, as many as 46 million (70%) suffer from some form of MSD. The condition—typically caused and/or aggravated by physical work—represents a huge and increasing cost to society. In EU member states, the annual cost is estimated to be EUR 240 billion, which represents a cost of up to 2% of total GDP.
Paolo Belluco, Head of R&D, LWT3, comments, “Our objective is to understand work-related MSD injuries so that we can work with industry partners to decrease their occurrence and impact. In doing so, we can reduce the costs to society and increase productivity, while ensuring better health outcomes, improved quality of life, and a stronger economy for all.”
In the initial stages of the new project, LWT3 set up a pilot scheme to gather and analyze data with industry partners. The goal was to measure and correlate physical movements and injuries, in order to build predictive models that could both inform best practices in industry and trigger warning signals about the risk of developing or aggravating MSD.
Paolo Belluco continues, “We designed and prototyped an advanced set of wearable sensors to monitor the position, movement, and strain on key muscles, and record how people execute their work in industrial settings. This generates huge data volumes.”
LWT3 wanted an analytics platform capable of anonymizing, aggregating, and correlating personal bio-mechanical and health data. As the company’s sensors harvest more data from more people, the predictive accuracy will increase. With massive scale in mind, the company looked for an analytics engine that could scale easily, and handle both batch and stream analysis.
LWT3 selected the Vertica Analytics Platform as the ideal start-small, grow-without limits solution for analyzing MSD-related data through its WINGS product. WINGS is an intelligent wearable system that uses custom electro pads to measure bio signals and movement, working with sensors in machinery to reveal muscle stress, strength, and fatigue in real time.
“We will be capturing very large data flows from wearable devices within very short timescales—even at the pilot stage,” remarks Paolo Belluco. “It was very important to us to build a scalable analytics solution right from the start, and Vertica (now OpenText) offers the capacity for these very large data sets that will give LWT3 predictive capabilities around MSD.”
To run its OpenText (formerly Vertica) solutions, LWT3 relies on an in-house hyper-converged data-center, with replication to a private cloud environment hosted by Gamma Studio, an Italian IT systems integrator and OpenText (formerly Vertica) technology partner in Milan. The hybrid model delivers high performance combined with the option to scale rapidly.
Paolo Belluco comments, “The Vertica (now OpenText) pricing model suits our business perfectly: The per-terabyte fee combines low initial costs with full clarity about our likely future spend as data volumes grow. In addition, VerticaPy brings many functions available in the Anaconda stack to Vertica (now OpenText), making it easy to use existing Python code and develop additional functionalities, essential for our plans to expand WINGS into other sectors.”
WINGS is a first-of-its-kind solution, so the direction in which LWT3 heads will be defined by initial results. The company therefore needs to be agnostic about the types of data it collects during the project, and how it processes that data. Paolo Belluco reports, “Vertica (now OpenText) gives us the ability to capture and work with any kind of data, so we are confident we have the right framework in place. It’s simple to move our data into Vertica (now OpenText), and the platform offers exceptional performance for the analysis of our anticipated data sets.”
Now that all the technical components are in place, LWT3 is working with industry partners to roll out the pilot and gather bio-signals from real-world workers. By analyzing billions upon billions of sensor data-points from 10,000 individuals, the company will be able to see in great detail how workers interact with the physical environment and machinery, and what impact this has on their bodies.
Vertica (now OpenText) gives LWT3 a flexible, high-capacity, high-performance analytics engine that can capture and process huge amounts of bio-mechanical data. We are confident that with Vertica (now OpenText) we have chosen the right framework for scalability and growth, capable of offering benefits right across society.
“Our goals are to reduce the incidence and severity of work-related MSD, and to enhance the way in which people work with machinery,” says Belluco. “By building and analyzing huge biometric data sets with Vertica (now OpenText), we can create best-practice approaches—for example, telling people the best way to lift a product or interact with a piece of manufacturing equipment. We can alert workers when their physical movement is putting them at risk of an injury.”
Using best practices derived from the analysis of real-world work, manufacturing businesses will be able to improve the efficiency and productivity of their processes, reduce injuries and related healthcare costs, cut the number of days lost to injury, and improve their reputation for safety. For employees, the benefits will be improved working conditions, reduced pain and discomfort, longer and healthier working lives, and improved quality of life during both employment and retirement. Moreover, reducing the incidence of MSD will result in significant reductions in healthcare costs and increases in GDP.
The WINGS wearable computer also has the potential to be used outside of industrial settings—for example, LWT3 plans to extend its use to wearable telemedicine. The system could be used by physiotherapists and occupational therapists to gather vital diagnostic information or to provide alerts on risky movements.
Paolo Belluco concludes, “Vertica (now OpenText) gives LWT3 a flexible, high-capacity, high-performance analytics engine that can capture and process huge amounts of bio-mechanical data. We are confident that with Vertica (now OpenText) we have chosen the right framework for scalability and growth, capable of offering benefits right across society.”
Founded by Human-Machine Interface specialists, LWT3 creates innovative solutions to enable biomechanical movement analysis, for almost any human activity from sports to music to manufacturing. The company combines its expertise in three key areas—data harvesting (IoT devices, bio-signals, prototyping), data processing (mining, machine learning, data fusion), and data visualization (dashboard, AR/VR, haptics)—to help organizations monitor and optimize biomechanics.