SkillWorx Assisted Worker is a SaaS offering that primarily addresses guidance and assistance use-case for field operations via tagging of physical space/object and remote mentoring for frontline workers where a hands-free experience is an invaluable approach because of the nature of their tasks and the need for improving the situational awareness of moving machinery, approaching forklifts or other vehicles, steam escape valves, slips, and trip hazards, electrical and chemical hazards etc.

​The major focus of the solution is to give frontline workers concise and clear knowledge of how to complete manual tasks and solve issues. To achieve this goal, the solution is built on the idea that a frontline worker is equipped with a head-mounted wearable device and one mentor at a time, where expertise is needed.

Mentor has a rich set of tools to help the frontline worker, but the message given is still concise and clear because they do not imagine that there is a part of such color and shape - the mentor marks the exact point of interest with a marker visible to the frontline. There is no other participant who can mark the wrong part by mistake - this way we achieve concise and clear information on how to solve this issue.

When it comes to complex infrastructure maintained by the frontline it may be hard to have deep knowledge about every single part for one person - then spectators come to play. They can participate in audio and video connections but cannot put markers on their own, so they do not introduce noise and unverified help to the frontline, and mistakes and misinterpretations are reduced.

SkillWorx Assisted Worker applies spatial intelligence to low-powered and head-mounted wearables devices, to assist front-line workers with vital up-to-date information on what to do, where, and how to complete work. Thanks to its real-time video analysis algorithms the solution recognizes and tracks the physical location of the worker and overlays spatial annotations during an audio/video session between a worker in the field and an experienced remote mentor.

GPS or radio triangulation systems can be easily affected at industrial sites by plant infrastructure interfering with the signal. Alternative, marker-based approaches are difficult to maintain. This is why we propose a positioning system that is 100% based on computer vision technology which gets the visual input from the physical world to construct a 3D map of points to make the surroundings understandable for machines.​

No matter if you are an end-user or solution vendor – our technology recognizes location of workers via visual input from their cameras or from streams or collections of frames from your SDK. ​