We are excited to bring Transform 2022 back on July 19th and literally July 20th – 28th. Join AI and data leaders for insightful conversations and exciting networking opportunities. Register Today!
Technology has a reputation for being impersonal. It’s easy to think of machine-driven artificial intelligence, 3D and biomechanics software as we would an episode of Netflix. black Mirror, But when pointed to the right problem, advanced data analytics solutions have the power to change human lives for the better.
take the job. Workers in practically every field – from shipping to pipefitting – are at risk of being physically compromised every day at work. More than half of manual workers compensation insurance claims are filed due to slips, trips and falls, as well as injuries related to lifting – including overextension and other poor body mechanics. Many of these problems can be avoided or corrected through proper lifting techniques, good posture and core strengthening.
How data analytics can assess biomechanics
how exactly? By providing track, analysis and timely feedback to the workers regarding their biomechanical form, communicated in simple words and in an easy-to-implement format. Repetitive movements are known to cause musculoskeletal strains or injuries, and when they are left unattended, their risk increases and more serious consequences are likely. But companies can achieve exponential performance gains in movement health while reducing injuries and maintaining a healthy workforce with just a few basic implementations.
For example, monitoring the displacement of the wrist and elbow in comparison to the hip joint will determine whether a worker is extending their arms. Tips can be given to employees to correct their form and to engage larger muscle groups over smaller muscle groups. Identifying the weight of boxes being moved will help refine AI algorithms, and workers can be sent real-time alerts or haptic feedback to their smartphones – everything from the direction of the moment (“putting one foot in front Make sure “second to weight bearing from the lower back to the hamstrings”) for individual strength and conditioning techniques.
In fact, working smartphones take a lot of load when it comes to maintaining the feedback loop, so to speak. Almost all manual laborers have access to one – and they may even be provided with a phone by the company. Workers may be asked (and encouraged) to stretch and participate in certain exercises as their smartphone tracks their movements to ensure perfection and proper form. In factory and distribution center environments, cameras can be installed throughout the work area to monitor and detect specific imbalances or instability. Feedback from that analysis—which includes company-explored exercises and connection strengthening for trainers or physical therapists—will be sent to each individual employee’s smartphone.
make life easier
Workers may be uncomfortable about these implementations. Some startups have taken to getting their employees to wear vests equipped with wearable trackers and sensors which, with good intentions, can be restrictive and take a psychological toll. (“Am I being watched?” an employee may ask himself. “Does the company not trust me?”) And from an operational standpoint, introducing new complications – daily sensor charging, employee compliance monitoring , Troubleshooting – More functions to manage. Shouldn’t technology make the work of workers easier?
AI can help. In fairness to labour, companies must maintain complete transparency about their intentions and the means of data collection. Chances are, that clarity and investment in less intrusive technology will be welcomed by employees who won’t need to attach sensors and will be highly scrutinized every workday. Computer vision technology is already included in the security measures of most large system environments. By not monitoring people’s worst behavior (theft, theft, false claims) using those cameras, companies are using these powers to track employee biomechanics, reduce workplace injuries, and improve worker well-being in workflows. can be customized. Keep employees healthy. Management lowers its insurance claims. Win-win
Is Big Brother watching?
Now, manual workers may have reason for artificial intelligence beyond surveillance concerns like Big Brother. For decades, workers ranging from factory line workers to packers have been looking for the rise of machines—and some have, in fact, lost work to automation. But some of that change is undeniably positive, in that heavy-assembly and high-risk environments once exposed workers to life-and-threatening machinery or hazardous chemicals and pollutants. Robotics are reducing injuries, as well as improving efficiency, for some of the repetitive-motion tasks previously performed by human workers.
In an ideal world, employees would be retrained in labor-intensive roles to tackle more creative and complex problem-solving tasks. Less-experienced workers will be able to develop skills quickly with AI-enhanced on-the-job training. In some cases, AI-equipped cameras are already augmenting rather than replacing human labor. By monitoring assembly-line production, tracking worker steps, and processing findings into actionable feedback, this data technology can provide valuable movement-efficiency training to employees on the line – including locations shared by humans and robots. involves moving and operating safely and efficiently.
Still who is paying the bill here? How do business owners benefit from the adoption (and of course, investment) of data technology? First and foremost is the benefit of reducing the hours of labor lost due to injuries and worker-compensation-related costs. But it also has the effect of fostering a healthier and (hopefully) happier workforce. Then the question becomes how to get the purchase and sale of labour. Most of us know that we must sit or stand tall to improve our posture, but often we are not obedient until an injury occurs. But perhaps simplifying the biomechanics and creating a reward system for completing the program and improving form could be the answer. By and large, imagine that every UPS or FedEx driver, assembly worker, and distribution center employee not only has access to, but is actively engaged with, movement-health-in-pocket technology. The industry as we know it will be changed overnight.
making AI successful
The key to making this a reality: a healthy mix of quantitative and qualitative data. For example, video is a great source of qualitative data. This resonates on platforms like Instagram and TikTok. On the other hand, data doesn’t lie. Marrying both – qualitative and quantitative information – is the most likely approach to deliver the results that companies are looking for. The seamless integration of these data streams is motivationally powerful, helping a worker to visualize, understand and translate their activities and the changes needed to address deficiencies and risk.
It’s too important to be left to chance – for workers and employers. Even among white-collar workers, improving posture reduces injuries, saves time away from work and allows for a more active and better off-hours and weekend lifestyle. As healthy workers and retirees get older, they are more likely to age—at home and in familiar and comfortable surroundings. This leads to an improved late-stage quality of life, free from loss of movement and restrictions imposed by a senior care facility.
Even if AI doesn’t save the world, it can save this assembly line worker from a rotator cuff tear and that picker from a slip disc. Data analytics has the power to help us grow healthier and ahead. And the better we move on, and the longer we keep well, the happier we will all be.
Sukemasa is the co-founder and CEO of Kabayama Utthan Labs,
data decision maker
Welcome to the VentureBeat community!
DataDecisionMakers is where experts, including the technical people who do data work, can share data-related insights and innovations.
Join us at DataDecisionMakers if you want to read about cutting-edge ideas and up-to-date information, best practices and the future of data and data technology.
You might even consider contributing an article of your own!
Read more from DataDecisionMakers
