Using AI to Scale Workplace Manual Handling Safety & Maximize Engagement

Is it possible to formalize and control the manual handling safety of all your workers on-site at the same time?

Before the likes of AI and wearable technology, no, this was not possible.
Typically, once a new starter has completed their manual handling training and has been signed off as trained for the job, they are on their own until the next scheduled training. This could be as long as a year! What about all the time in between?

Even for a seasoned worker, how can you be in all places at once, monitoring and making sure adherence to manual handling safety is being practiced? How does your worker even know? We are not always aware of how we are moving throughout the course of a day.

Furthermore, spotting ‘one’ unsafe posture is not going to cause injury, how would you be able to spot an incorrect or unsafe posture that has been repeated multiple times or even for months?

In the same vein, there is no denying the direct relationship between safety and productivity. Any ultra-time-driven businesses squeezing output from their workers are aware of the pressure and the ripple effect put on the entire organization when injuries or lack of engagement occurs.

Soter Analytics, a global leading safety technology developer specializes in developing AI-driven safety products to build worker engagement, increase staff retention, and maximize productivity safely. The personalized nature of their technology allows workers to monitor and learn about their own movement safety while on the job, at any time, giving them the training required to prevent injuries from occurring.

The Soter technology is individualized and has been built for the workers, not the organizations. However, the aftereffect of workers using the products brings proven results to businesses, increasing engagement and safety culture and decreasing lost-time injuries through reducing up to 55% of injuries. The data collected is able to be used by both workers and management, promoting comradeship and a common goal, increasing morale and trust helping to break down any silos between management and those on the ground.

The technology forges a formalized process for workers with objective data to monitor, coach, and support each employee in compliance with manual handling activities. Making it possible to assist all seasoned workers or new starters across a range of locations and roles and covering any chosen time frame all at once

So how do these technologies work?

Firstly, the Soter Device is used by the workers to collect data and for them to gain awareness of safe movement postures which incites behavioral change.

SoterTask is then brought in second to dive deeper into any tasks that are high risk and resistant to behavioral change - as shown by the data from the wearables.
1. The Soter Device is a small matchbox size wearable that clips onto any existing hardware worn by the worker, typically for around 12-20 days. It can be attached to a shirt collar, headset, or helmet for example. The smart device learns the worker via clever machine learning algorithms and provides real-time biofeedback when they are in an unsafe posture. Just like most personalized wearables, the data is collected and available via a user-friendly app for improvement tracking and data visuals.

2. SoterTask is a vision processing technology that provides further insight into job task movement behavior. A video of any task being performed is all that is required and once processed a detailed highlighted overlay and report shows risk areas in the body for improvement requirements.

Both solutions

• Are scalable and able to be easily distributed across dispersed locations and sites
• Give workers the individual training they need to move safely - on the job, limiting downtime and providing real work activities for generating improvement practices
• Incite permanent behavioral change using scientifically proven biofeedback awareness indicators
• Encourage and engage workers in their safety promoting ownership and increasing safety culture

Using Leading indicators for measuring engagement

The technology and collected data provide easy to gauge strengths and weaknesses of safety efforts to assist with future successes.

• The collection of quality datasets enables the implementation of long-term improvements to manage injury risk
• Self-reported improvement by workers doing the program and engagement with the self-managed learning via biofeedback and in-app manual handling tutorials
• Recognition of potentially hazardous jobs tasks being performed and pro-active requests from workers to use the Soter devices and/or SoterTask to capture the risk profile prior to an injury occurring
• Workers pro-actively making changes to adopt protective behaviors and safer postures from learning about their own risk
• Existing injury management resources moving into the preventative, early intervention space and making changes to the risk level of roles based on injury reduction data