By understanding the activity a team of people is doing along with their location, opportunities to remove frustrations to the workforce can be identified. The data can be used directly to make the teams more successful on the work front as well as better understand the driving forces behind good or bad progress or even the implications of external factors such as hiring of new staff, introduction of new projects or even the seasonal variation of the weather and how this impacts the work.
Safeguard can deliver data right into the foreman’s hands to allow him to make better data-driven decisions which help his team have more successful days.
Using deep learning architectures, Safeguard can understand what industrial activities the wearer is performing throughout their day. This can be used to understand metrics like ‘spark’ time a team of welders has completed or the exact duration a grinder has been using his machine so that Hand and Arm Vibration Syndrome can be assessed.
Safeguard can understand the location of an individual in an indoor and outdoor environment and communicate this in real time. This can be used to locate a stricken worker or automate your mustering process for drills or emergencies.
Undertanding the location of an individual along with his or her activity, Safeguard can build machine learning models to ensure the right person is in the right place at the right time, improving efficiency.
Understanding the position of the materials alongside the activity and location of the individual, effective manhours spent on a particular piece of work can be understood unlocking valuable insights into progress and schedule.