Artificial Intelligence Applications to Smart City and Smart Enterprise
Impedovo, Donato
Artificial Intelligence Applications to Smart City and Smart Enterprise - Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2020 - 1 electronic resource (374 p.)
Open Access
Smart cities operate under more resource-efficient management and economy than ordinary cities. As such, advanced business models have emerged around smart cities, which led to the creation of smart enterprises and organizations that depend on advanced technologies. This book includes 21 selected and peer-reviewed articles contributed in the wide spectrum of artificial intelligence applications to smart cities. Chapters refer to the following areas of interest: vehicular traffic prediction, social big data analysis, smart city management, driving and routing, localization, safety, health, and life quality.
Creative Commons
English
9783039364374 9783039364381
Искусственный интеллект
spatio-temporal residual networks bus traffic flow prediction advance rate shield performance principal component analysis ANFIS-GA tunnel online learning extreme learning machine cyclic dynamics transfer learning knowledge preservation Feature Adaptive optimization Bacterial Foraging algorithm Swarm Intelligence algorithm Isolated Microgrid traffic surveillance video state analysis Grassmann manifold neural network machine-learning quality of life Better Life Index bagging ensemble learning pedestrian attributes surveillance image semantic attributes recognition multi-label learning large-scale database traffic congestion detection minimizing traffic congestion traffic prediction deep learning urban mobility ITS Vehicle-to-Infrastructure neural networks LSTM embeddings trajectories motion behavior smart tourism driver’s behavior detection texting and driving convolutional neural network smart car smart cities smart infotainment driver distraction cameras convolution detection image recognition DSS diabetes prediction homecare assistance information system muti-attribute analysis artificial training dataset machine learning big data data analysis sensors Internet of Things vehicular networks VDTN routing message scheduling traffic flow prediction wavenet TrafficWave RNN GRU SAEs risk assessment neural architecture search recurrent neural network automated driving vehicle decision support system artificial intelligence disaster management Smart city program management integrated model smart city intelligence transportation system computer vision potential pedestrian safety data mining healthcare Apache Spark disease detection symptoms detection Arabic language Saudi dialect Twitter high performance computing (HPC) spatial-temporal dependencies traffic periodicity graph convolutional network traffic speed prediction vehicular traffic surveillance video big data analysis autonomous driving life quality pattern recognition
004.8
Artificial Intelligence Applications to Smart City and Smart Enterprise - Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2020 - 1 electronic resource (374 p.)
Open Access
Smart cities operate under more resource-efficient management and economy than ordinary cities. As such, advanced business models have emerged around smart cities, which led to the creation of smart enterprises and organizations that depend on advanced technologies. This book includes 21 selected and peer-reviewed articles contributed in the wide spectrum of artificial intelligence applications to smart cities. Chapters refer to the following areas of interest: vehicular traffic prediction, social big data analysis, smart city management, driving and routing, localization, safety, health, and life quality.
Creative Commons
English
9783039364374 9783039364381
Искусственный интеллект
spatio-temporal residual networks bus traffic flow prediction advance rate shield performance principal component analysis ANFIS-GA tunnel online learning extreme learning machine cyclic dynamics transfer learning knowledge preservation Feature Adaptive optimization Bacterial Foraging algorithm Swarm Intelligence algorithm Isolated Microgrid traffic surveillance video state analysis Grassmann manifold neural network machine-learning quality of life Better Life Index bagging ensemble learning pedestrian attributes surveillance image semantic attributes recognition multi-label learning large-scale database traffic congestion detection minimizing traffic congestion traffic prediction deep learning urban mobility ITS Vehicle-to-Infrastructure neural networks LSTM embeddings trajectories motion behavior smart tourism driver’s behavior detection texting and driving convolutional neural network smart car smart cities smart infotainment driver distraction cameras convolution detection image recognition DSS diabetes prediction homecare assistance information system muti-attribute analysis artificial training dataset machine learning big data data analysis sensors Internet of Things vehicular networks VDTN routing message scheduling traffic flow prediction wavenet TrafficWave RNN GRU SAEs risk assessment neural architecture search recurrent neural network automated driving vehicle decision support system artificial intelligence disaster management Smart city program management integrated model smart city intelligence transportation system computer vision potential pedestrian safety data mining healthcare Apache Spark disease detection symptoms detection Arabic language Saudi dialect Twitter high performance computing (HPC) spatial-temporal dependencies traffic periodicity graph convolutional network traffic speed prediction vehicular traffic surveillance video big data analysis autonomous driving life quality pattern recognition
004.8