Camera Based positioning and safety

The EPS RTLS system

Essensium has built up a substantial expertise when it comes to the use of RTLS (Real Time Location Systems) technology. The EPS (Essensium Positioning System) RTLS system uses camera based technology sometimes complemented by AI (Artificial Intelligence) that constantly monitors the positions of tracked vehicles and pedestrians within the premises of the warehouse or the industrial site.


We install specially developed EPS devices inside each forklift so the driver gets the information presented in real time via the camera technology that is installed throughout the different locations. The data is transferred to a central server for analytical purposes so the customer can review all operational elements. This allows for a full view on operations, understand the busiest locations, potential dangerous situations and the main reasons of these dangerous situations and so many much more.

Fully Configurable

When extended with all options, the user has the possibility to configure individual safety zones for each vehicle depending on parameters such as:

  • Size, weight and type of vehicle
  • Current speed
  • Number of vehicles nearby
  • Location
  • Time of day or night
  • Certification or training level of operator assigned to vehicle

Quick Start

Site Survey

Define the area to secure

  • Loading docks
  • Narrow aisles
  • Low visibility areas

Equip vehicle

Just tell us how many you need

  • Compatible with any type of vehicle
  • Compatible with vendor features like speed reduction

Enjoy being safe

Your work environment is now safer

  • Customizable safety distances
  • Customizable alerting
  • Extensible with minimal investment

Artificial Intelligence

Essensium uses AI or Artificial Intelligence as part of its SafeTrack Pedestrians solution. The AI supports the identification of pedestrians close to the forklifts to understand their exact position and alarm the forklift driver of a potential unsafe situation.

But AI goes further, it allows us to predict situations based on historical data but it also helps to analyze what the different users are doing so we better understand the environment where pedestrians and vehicles move in, allowing us to better predict situations like human movement and avoid any potential dangerous situations.