Order Total (1 Item Items):
Shipping Destination:
Smart Cities Machine Learning (236 results)
Skip to main search results
Search filters
Product Type
- All Product Types
- Books (236)
- Magazines & Periodicals (No further results match this refinement)
- Comics (No further results match this refinement)
- Sheet Music (No further results match this refinement)
- Art, Prints & Posters (No further results match this refinement)
- Photographs (No further results match this refinement)
- Maps (No further results match this refinement)
- Manuscripts & Paper Collectibles (No further results match this refinement)
Condition Learn more
- New (220)
- As New, Fine or Near Fine (11)
- Very Good or Good (1)
- Fair or Poor (No further results match this refinement)
- As Described (4)
Collectible Attributes
- First Edition (2)
- Signed (No further results match this refinement)
- Dust Jacket (No further results match this refinement)
- Seller-Supplied Images (107)
- Not Print on Demand (123)
Language (2)
Free Shipping
Seller Location
Seller Rating
-
-
Proceedings of International Conference on Recent Trends in Machine Learning, IoT, Smart Cities and Applications. ICMISC 2020.
Book 465 of 540: Advances in Intelligent Systems and ComputingLanguage: English
Published by Singapore, Springer., 2021
ISBN 10: 981157233X ISBN 13: 9789811572333
Seller: Universitätsbuchhandlung Herta Hold GmbH, Berlin, Germany
Association Member: GIAQ ILAB VDA
Seller rating 4 out of 5 stars
XVII, 998 p. Softcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Advances in Intelligent Systems and Computing, 1245. Sprache: Englisch.
-
Condition: As New. Unread book in perfect condition.
-
Condition: As New. Unread book in perfect condition.
-
Proceedings of 3rd International Conference on Recent Trends in Machine Learning, IoT, Smart Cities and Applications: ICMISC 2022
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
£ 45.35
£ 11.98 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. In.
-
Machine Learning for Environmental Noise Classification in Smart Cities (Hardcover)
Language: English
Published by Springer International Publishing AG, Cham, 2024
ISBN 10: 3031546660 ISBN 13: 9783031546662
Hardcover. Condition: new. Hardcover. We present a Machine Learning (ML) approach to monitoring and classifying noise pollution. Both methods of monitoring and classification have been proven successful. MATLAB and Python code was generated to monitor all types of noise pollution from the collected data, while ML was trained to classify these data. ML algorithms showed promising performance in monitoring the different sound classes such as highways, railways, trains and birds, airports and many more. It is observed that all the data obtained by both methods can be used to control noise pollution levels and for data analytics. They can help decision making and policy making by stakeholders such as municipalities, housing authorities and urban planners in smart cities. The findings indicate that ML can be used effectively in monitoring and measurement. Improvements can be obtained by enhancing the data collection methods. The intention is to develop more ML platforms from which to construct a less noisy. The second objective of this study was to visualize and analyze the data of 18 types of noise pollution that have been collected from 16 different locations in Malaysia. All the collected data were stored in Tableau software. Through the use of both qualitative and quantitative measurements, the data collected for this project was then combined to create a noise map database that can help smart cities make informed decisions. We present a Machine Learning (ML) approach to monitoring and classifying noise pollution. MATLAB and Python code was generated to monitor all types of noise pollution from the collected data, while ML was trained to classify these data. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
-
-
Condition: New. 2024th edition NO-PA16APR2015-KAP.
-
Internet of Energy for Smart Cities : Machine Learning Models and Techniques
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: As New. Unread book in perfect condition.
-
Artificial Intelligence, Machine Learning, and Optimization Tools for Smart Cities: Designing for Sustainability (Springer Optimization and Its Applications)
Book 172 of 176: Springer Optimization and Its ApplicationsSeller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
£ 58.56
£ 11.98 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. In.
-
Artificial Intelligence, Machine Learning, and Optimization Tools for Smart Cities: Designing for Sustainability (Springer Optimization and Its Applications, 186)
Book 172 of 176: Springer Optimization and Its ApplicationsSeller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
£ 58.56
£ 11.98 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. In.
-
Internet of Energy for Smart Cities : Machine Learning Models and Techniques
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: New.
-
Internet of Energy for Smart Cities: Machine Learning Models and Techniques
Language: English
Published by Taylor & Francis Ltd, 2024
ISBN 10: 036749955X ISBN 13: 9780367499556
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Seller rating 5 out of 5 stars
Paperback / softback. Condition: New. New copy - Usually dispatched within 4 working days.
-
Hardcover. Condition: Brand New. 187 pages. 9.25x6.10x9.45 inches. In Stock.
-
Condition: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
-
Role Of big Data and Machine Learning In Development of Smart Cities
Language: English
Published by LAP LAMBERT Academic Publishing, 2021
ISBN 10: 6203924490 ISBN 13: 9786203924497
Taschenbuch. Condition: Neu. Role Of big Data and Machine Learning In Development of Smart Cities | Hiba Iftikhar | Taschenbuch | Englisch | 2021 | LAP LAMBERT Academic Publishing | EAN 9786203924497 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
-
Paperback. Condition: Brand New. 322 pages. 9.18x6.12x9.21 inches. In Stock.
-
Condition: New. 1st ed. 2022 edition NO-PA16APR2015-KAP.
-
-
Machine Learning for Environmental Noise Classification in Smart Cities
Language: English
Published by Springer Nature Switzerland, Springer Nature Switzerland, 2025
ISBN 10: 3031546695 ISBN 13: 9783031546693
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - We present a Machine Learning (ML) approach to monitoring and classifying noise pollution. Both methods of monitoring and classification have been proven successful. MATLAB and Python code was generated to monitor all types of noise pollution from the collected data, while ML was trained to classify these data. ML algorithms showed promising performance in monitoring the different sound classes such as highways, railways, trains and birds, airports and many more. It is observed that all the data obtained by both methods can be used to control noise pollution levels and for data analytics. They can help decision making and policy making by stakeholders such as municipalities, housing authorities and urban planners in smart cities. The findings indicate that ML can be used effectively in monitoring and measurement. Improvements can be obtained by enhancing the data collection methods. The intention is to develop more ML platforms from which to construct a less noisy. The second objective of this study was to visualize and analyze the data of 18 types of noise pollution that have been collected from 16 different locations in Malaysia. All the collected data were stored in Tableau software. Through the use of both qualitative and quantitative measurements, the data collected for this project was then combined to create a noise map database that can help smart cities make informed decisions.
-
Machine Learning for Environmental Noise Classification in Smart Cities
Language: English
Published by Springer Nature Switzerland, Springer International Publishing, 2024
ISBN 10: 3031546660 ISBN 13: 9783031546662
Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - We present a Machine Learning (ML) approach to monitoring and classifying noise pollution. Both methods of monitoring and classification have been proven successful. MATLAB and Python code was generated to monitor all types of noise pollution from the collected data, while ML was trained to classify these data. ML algorithms showed promising performance in monitoring the different sound classes such as highways, railways, trains and birds, airports and many more. It is observed that all the data obtained by both methods can be used to control noise pollution levels and for data analytics. They can help decision making and policy making by stakeholders such as municipalities, housing authorities and urban planners in smart cities. The findings indicate that ML can be used effectively in monitoring and measurement. Improvements can be obtained by enhancing the data collection methods. The intention is to develop more ML platforms from which to construct a less noisy. The second objective of this study was to visualize and analyze the data of 18 types of noise pollution that have been collected from 16 different locations in Malaysia. All the collected data were stored in Tableau software. Through the use of both qualitative and quantitative measurements, the data collected for this project was then combined to create a noise map database that can help smart cities make informed decisions.
-
Taschenbuch. Condition: Neu. Machine Learning for Environmental Noise Classification in Smart Cities | Ali Othman Albaji | Taschenbuch | Synthesis Lectures on Engineering, Science, and Technology | xvii | Englisch | 2025 | Springer | EAN 9783031546693 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
-
-
-
Proceedings of the 2nd International Conference on Recent Trends in Machine Learning, IoT, Smart Cities and Applications : ICMISC 2021
Book 340 of 391: Lecture Notes in Networks and SystemsLanguage: English
Published by Springer Nature Singapore, 2022
ISBN 10: 9811664064 ISBN 13: 9789811664069
Condition: Gut. Zustand: Gut | Seiten: 856 | Sprache: Englisch | Produktart: Bücher | This book contains original, peer-reviewed research articles from the Second International Conference on Recent Trends in Machine Learning, IoT, Smart Cities and Applications, held in March 28-29th 2021 at CMR Institute of Technology, Hyderabad, Telangana India. It covers the latest research trends and developments in areas of machine learning, artificial intelligence, neural networks, cyber-physical systems, cybernetics, with emphasis on applications in smart cities, Internet of Things, practical data science and cognition. The book focuses on the comprehensive tenets of artificial intelligence, machine learning and deep learning to emphasize its use in modelling, identification, optimization, prediction, forecasting and control of future intelligent systems. Submissions were solicited of unpublished material, and present in-depth fundamental research contributions from a methodological/application perspective in understanding artificial intelligence and machine learning approaches and their capabilities in solving a diverse range of problems in industries and its real-world applications.
-
-
IoT and WSN based Smart Cities: A Machine Learning Perspective (Hardcover)
Book 117 of 129: EAI/Springer Innovations in Communication and ComputingLanguage: English
Published by Springer Nature Switzerland AG, Cham, 2022
ISBN 10: 3030841812 ISBN 13: 9783030841812
Hardcover. Condition: new. Hardcover. This book provides an investigative approach to how machine learning is helping to maintain and secure smart cities, including principal uses such as smart monitoring, privacy, reliability, and public protection. The authors cover important areas and issues around implementation roadblocks, ideas, and opportunities in smart city development. The authors also include new algorithms, architectures and platforms that can accelerate the growth of smart city concepts and applications. Moreover, this book provides details on specific applications and case studies related to smart city infrastructures, big data management, and prediction techniques using machine learning. This book provides an investigative approach to how machine learning is helping to maintain and secure smart cities, including principal uses such as smart monitoring, privacy, reliability, and public protection. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
-
-
-
Condition: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | This volume offers a wealth of interdisciplinary approaches to artificial intelligence, machine learning and optimization tools, which contribute to the optimization of urban features towards forming smart, sustainable, and livable future cities.Special features include:New research on the design of city elements and smart systems with respect to new technologies and scientific thinkingDiscussions on the theoretical background that lead to smart cities for the futureNew technologies and principles of research that can promote ideas of artificial intelligence and machine learning in optimized urban environmentsThe book engages students and researchers in the subjects of artificial intelligence, machine learning, and optimization tools in smart sustainable cities as eminent international experts contribute their research results and thinking in its chapters. Overall, its audience can benefit from a variety of disciplines including, architecture, engineering, physics, mathematics, computer science, and related fields.
