Smart Solutions for Safety and Health

What is Smart Safety?

During the revolution of Industry 4.0, current technological advancements has been leading to better understand the working conditions in workplaces and help optimize the productivity and efficiency, while enhancing the quality of life of millions of workers. We can make your workplace smarter and safer by utilizing robotics, sensors and IoT (Internet of Things) concept together with the recent machine learning and data mining methods.

We can develop automated tools and systems equipped with sensors and actuators to prevent accidents, injuries, and diseases.

Real-time monitoring of the workplace with different sensors and cameras help us understand the workplace conditions. We can remotely detect and identify humans with their basic health conditions, detect other objects and machineries with their physical properties. Utilizing machine learning, we can remotely detect team behavior (normal working, emergency-running people, and no motion) and incidents. Yet, we can even predict incidents before they occur.

  • International Labor Organization (ILO) estimates each year around the globe 313 million non-fatal and 350,000 fatal occupational accidents happen at work.
  • 160 million non-fatal occupational diseases occur and fatal work-related diseases cause 2 million deaths.
  • The total costs is approximately 4% of the world’s annual GDP (~2.8 trillion dollars).
  • Therefore, companies should focus to prevent not only the occupational diseases but also work-related diseases.

Custom Solutions

  • Tell us what you need! We can describe the problem and the situation together in a kick-off workshop and decide how to start.
  • Let’s see together! Our researchers inspect on-site, analyze existing data, and make preliminary evaluation by collecting various data:
    • Displacement, velocity, and vital signs (e.g. breath and heart rates, body motions) by radar technologies
    • RGB, thermal, multispectral, and depth images
    • Temperature, humidity, sound, gas level, acceleration and angular velocity of objects
  • How to proceed! After evaluating the preliminary inspection in an intermittent workshop we can focus on one of the two actions or both:
    • Behavioral safety: to prevent accidents and injuries to influence employee actions
    • Predictive analysis: to predict present and future using historical big data
  • Implementation

In the fireplace, thermal imaging cameras are used to find people who need help. These cameras can penetrate thick smoke but can only map a two-dimensional temperature. Therefore, the firefighters have no knowledge of three-dimensional information and they can hardly estimate local conditions.

Fusion of sensory data from radar and inertial measurement unit sensors provides distance, position, and orientation information which later superposed on the infrared image. The implemented sensor fusion filter for navigation could run with a position accuracy of 5 cm sufficiently accurate trajectories so that a combination of 2D radar and 3D infrared data was possible.

FeuerWERR project enabled a novel, portable, firefighter-friendly add-on to thermal imaging cameras by which the depth information is linked to heat images. This novel device helps the firefighters to minimize the cognitive burden of the firefighters.

Downloads

Real-Time Capable μ-Doppler Decomposition of Walking Human Limbs

Micro-Doppler Based Human-Robot Classification Using Ensemble and Deep Learning Approaches

Person Identification and Body Mass Index: A Deep Learning-Based Study on Micro-Dopplers