Transport scientists at TU Dresden are developing a system for greater sustainability in cooperation with two industrial partners.

In the forestry industry, it is a common practice to open up potential new fields of work with the help of current IoT technologies (Internet of Things). In a project by the Chair of Transport Systems Information Technology (iTVS) at TU Dresden, the latter is creating an assistance system that is intended to help increase the efficiency of forestry machinery. In addition, a safety system for forestry workers is being designed.

The chair is supported by two industrial partners: Metirionic and Trans4mation IT GmbH. For the project, wireless sensor networks (WSN) will be applied in the forestry context in the following scenarios:

  • Assistance system with optimised path planning
  • Safety system to warn operators in forestry vehicles when a forestry worker enters the danger zone (analogous to the blind spot assistant in the automotive sector)

One of the project challenges is the limitation of the satellite navigation system for more precise location determination in more densely overgrown forests.

The two partners mentioned above support the project by analysing the spatial relationships between the various account points of the radio system together with the iTVS and with the help of algorithms generated in-house. The basis for locating people (forestry workers) or objects (trees, harvesters) is distance and angle information. Based on this information, robust positioning algorithms are generated and integrated into the system. Overall, the use of the two systems primarily prevents otherwise erroneous angle and distance measurement by radio-based applications.

Harvester Navi, as a universal and infrastructure-free localisation and warning system, is not only suitable for the case described, but could also be used in other fields of application.



Prof. Dr.-Ing. Oliver Michler
Head of the Chair of Transport Systems Information Technology
"Friedrich List" Faculty of Transport and Traffic Sciences, TU Dresden