The book is about real-time infrastructure monitoring and safety using vibration and tilt sensors at urban scale integrated with IoT and has the core of machine learning algorithms for event detection and decision making. This work focused on comprehensive study, design, fabrication, testing, calibration, and deployment of industry-grade sensor nodes with extremely high resolution sensing to ensure trustable warnings against exceeding permissible site limits and call for intervention. The major demands in disaster monitoring consist of flexible deployment, system scalability, and fast retrieval of data to quickly locate hazardous areas (or eventual collapses).
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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The book is about real-time infrastructure monitoring and safety using vibration and tilt sensors at urban scale integrated with IoT and has the core of machine learning algorithms for event detection and decision making. This work focused on comprehensive study, design, fabrication, testing, calibration, and deployment of industry-grade sensor nodes with extremely high resolution sensing to ensure trustable warnings against exceeding permissible site limits and call for intervention. The major demands in disaster monitoring consist of flexible deployment, system scalability, and fast retrieval of data to quickly locate hazardous areas (or eventual collapses). 84 pp. Englisch. N° de réf. du vendeur 9786204750774
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Vendeur : moluna, Greven, Allemagne
Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. The book is about real-time infrastructure monitoring and safety using vibration and tilt sensors at urban scale integrated with IoT and has the core of machine learning algorithms for event detection and decision making. This work focused on comprehensive . N° de réf. du vendeur 692529507
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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -The book is about real-time infrastructure monitoring and safety using vibration and tilt sensors at urban scale integrated with IoT and has the core of machine learning algorithms for event detection and decision making. This work focused on comprehensive study, design, fabrication, testing, calibration, and deployment of industry-grade sensor nodes with extremely high resolution sensing to ensure trustable warnings against exceeding permissible site limits and call for intervention. The major demands in disaster monitoring consist of flexible deployment, system scalability, and fast retrieval of data to quickly locate hazardous areas (or eventual collapses).VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 84 pp. Englisch. N° de réf. du vendeur 9786204750774
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Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The book is about real-time infrastructure monitoring and safety using vibration and tilt sensors at urban scale integrated with IoT and has the core of machine learning algorithms for event detection and decision making. This work focused on comprehensive study, design, fabrication, testing, calibration, and deployment of industry-grade sensor nodes with extremely high resolution sensing to ensure trustable warnings against exceeding permissible site limits and call for intervention. The major demands in disaster monitoring consist of flexible deployment, system scalability, and fast retrieval of data to quickly locate hazardous areas (or eventual collapses). N° de réf. du vendeur 9786204750774
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Vendeur : preigu, Osnabrück, Allemagne
Taschenbuch. Etat : Neu. Real-time Urban Scale Early Warning using Structural Health Monitoring | IoT Systems | Farid Touati (u. a.) | Taschenbuch | Englisch | 2022 | LAP LAMBERT Academic Publishing | EAN 9786204750774 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand. N° de réf. du vendeur 123354580
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