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Implementation of Sensors and Artificial Intelligence for Environmental Hazards Assessment in Urban, Agriculture and Forestry Systems
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The implementation of artificial intelligence (AI), together with robotics, sensors, sensor networks, Internet of Things (IoT), and machine/deep learning modeling, has reached the forefront of research activities, moving towards the goal of increasing the efficiency in a multitude of applications and purposes related to environmental sciences. The development and deployment of AI tools requires specific considerations, approaches, and methodologies for their effective and accurate applications. This Special Issue focused on the applications of AI to environmental systems related to hazard assessment in urban, agriculture, and forestry areas.
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Keywords
- Animal welfare
- artificial intelligence
- Artificial Neural Networks
- Automation
- Climate Change
- climate-smart agriculture
- Computer vision
- electronic nose
- GIS
- Heart Rate
- heat stress
- History of engineering & technology
- Land use
- leaf area index
- Machine learning
- Markov chain
- n/a
- near-infrared spectroscopy
- Neural Network
- parallel computing
- photosynthesis modeling
- plant water status modeling
- random forest
- random forests
- Remote sensing
- respiration rate
- Sensor networks
- skin temperature
- smart agriculture
- smart village
- smoke taint
- sustainability
- Tabriz City
- Technology
- Technology, engineering, agriculture
- Technology: general issues
- tree monitoring
- tree water stress index
- urban information
- urban tree management
- volatile compounds
- volatile phenols
- water distribution networks
- water network contamination
- water network pollution
- wine sensory
Links
DOI: 10.3390/books978-3-0365-2905-9Editions