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Sensors for Digital Transformation in Smart Forestry.

Florian Ehrlich-Sommer1, Ferdinand Hoenigsberger1, Christoph Gollob2

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Smart forestry uses artificial intelligence (AI) for better forest management. High-quality sensor data, collected by autonomous robots and guided by human experts, is crucial for AI

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Area of Science:

  • Forestry Science
  • Artificial Intelligence
  • Robotics
  • Sensor Technology

Background:

  • Smart forestry, driven by artificial intelligence (AI), promises enhanced forest management and reduced environmental impact.
  • Effective AI implementation in forestry relies heavily on the availability of extensive, high-quality data.
  • Challenging forest environments pose significant obstacles to traditional data collection methods.

Purpose of the Study:

  • To highlight the critical role of sensor-based data acquisition in the digital transformation of forestry.
  • To emphasize the integration of sensor technologies for standardized, high-quality data generation essential for AI.
  • To explore the synergy between human expertise and digital transformation through a human-in-the-loop approach.

Main Methods:

  • Deployment of autonomous robotic systems for data collection and processing within forest environments.
  • Integration of a universal sensor platform to facilitate sensor deployment and data generation.
  • Implementation of a human-in-the-loop approach for expert-guided data generation and adaptability.

Main Results:

  • Autonomous robotic systems effectively function as mobile data collectors and processing hubs in forests.
  • The universal sensor platform aids in sensor integration and the generation of substantial volumes of quality data.
  • The initial phase of data generation is critical for successful digital transformation in forestry.

Conclusions:

  • Comprehensive, high-quality data generation is the cornerstone of advancing smart forestry.
  • The careful selection of appropriate sensors is paramount for the success of AI applications in forestry.
  • Integrating human expertise with autonomous systems enhances the adaptability and effectiveness of smart forestry initiatives.