Implementation of Sensors and Artificial Intelligence for Environmental Hazards Assessment in Urban, Agriculture and Forestry Systems

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 an...

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Other Authors: Fuentes, Sigfredo (Editor), Unnithan, Ranjith R (Editor), Tongson, Eden (Editor), Lipovetzky, Nir (Editor)
Format: Book Chapter
Published: Basel MDPI - Multidisciplinary Digital Publishing Institute 2022
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Online Access:Get Fullteks
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100 1 |a Fuentes, Sigfredo  |4 edt 
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700 1 |a Tongson, Eden  |4 edt 
700 1 |a Lipovetzky, Nir  |4 edt 
700 1 |a Fuentes, Sigfredo  |4 oth 
700 1 |a Unnithan, Ranjith R  |4 oth 
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245 1 0 |a Implementation of Sensors and Artificial Intelligence for Environmental Hazards Assessment in Urban, Agriculture and Forestry Systems 
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300 |a 1 electronic resource (206 p.) 
506 0 |a Open Access  |2 star  |f Unrestricted online access 
520 |a 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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546 |a English 
650 7 |a History of engineering & technology  |2 bicssc 
653 |a machine learning 
653 |a artificial neural networks 
653 |a random forests 
653 |a water network pollution 
653 |a sensor networks 
653 |a parallel computing 
653 |a heat stress 
653 |a animal welfare 
653 |a climate change 
653 |a automation 
653 |a smoke taint 
653 |a remote sensing 
653 |a near-infrared spectroscopy 
653 |a volatile phenols 
653 |a electronic nose 
653 |a wine sensory 
653 |a smart village 
653 |a smart agriculture 
653 |a climate-smart agriculture 
653 |a technology 
653 |a sustainability 
653 |a skin temperature 
653 |a artificial intelligence 
653 |a heart rate 
653 |a respiration rate 
653 |a GIS 
653 |a Markov chain 
653 |a land use 
653 |a urban information 
653 |a Tabriz City 
653 |a water distribution networks 
653 |a water network contamination 
653 |a random forest 
653 |a neural network 
653 |a urban tree management 
653 |a tree monitoring 
653 |a computer vision 
653 |a tree water stress index 
653 |a leaf area index 
653 |a volatile compounds 
653 |a photosynthesis modeling 
653 |a plant water status modeling 
653 |a n/a 
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856 4 0 |a www.oapen.org  |u https://directory.doabooks.org/handle/20.500.12854/78781  |7 0  |z DOAB: description of the publication