Artificial Intelligence-Powered Sensors in Smart Agriculture and Precision Forestry
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".
Deadline for manuscript submissions: closed (25 July 2024) | Viewed by 2322
Special Issue Editor
Interests: precision agriculture; machine learning; deep learning; precision forestry; condensed matter physics; spectroscopy
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The improvements brought by AI technologies in smart agriculture and precision forestry have the potential to increase productivity, reduce waste, and improve sustainability. Indeed, AI-powered sensors can grant a complete map of the culture, allowing for informed decisions about fertilization, irrigation, and pest control, resulting in improved crop yields and more efficient use of resources. AI applications to precision forestry can be used to analyze signals collected by remote and proximal sensors, allowing the precise identification of areas that are at risk of disease or wildfire and the development of targeted strategies for managing these risks. Finally, AI-based signal analysis can be used also to improve work safety during in-field operations.
This Special Issue will address all types of AI-powered sensors applied to smart agriculture and precision forestry.
Dr. Luciano Ortenzi
Guest Editor
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Keywords
- machine learning
- deep learning
- pattern recognition
- image classification
- image segmentation
- object detection
- hyperspectral and multispectral signals
- thermal images
- proximal sensing
- remote sensing
- smart agriculture
- smart pruning
- precision forestry
- animal tracking
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