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AI, IoT, Big Data and Cloud Computing for Industry 4.0 / / edited by Amy Neustein, Parikshit N. Mahalle, Prachi Joshi, Gitanjali Rahul Shinde
AI, IoT, Big Data and Cloud Computing for Industry 4.0 / / edited by Amy Neustein, Parikshit N. Mahalle, Prachi Joshi, Gitanjali Rahul Shinde
Autore Neustein Amy
Edizione [1st ed. 2023.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023
Descrizione fisica 1 online resource (589 pages)
Disciplina 658.40380285
Altri autori (Persone) MahalleParikshit N
JoshiPrachi
ShindeGitanjali Rahul
Collana Signals and Communication Technology
Soggetto topico Computational intelligence
Telecommunication
Artificial intelligence
Computational Intelligence
Communications Engineering, Networks
Artificial Intelligence
ISBN 3-031-29713-X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Introduction -- Section 1: Fundamentals of the Industry 4.0 -- Fundamental of IoT -- Architecture of IoT -- Automation -- Big data challenges -- Cloud computing services -- convergence of IoT and cloud computing -- Section 2: Emerging trends in Artificial Intelligence -- Knowledge representation -- Machine learning -- Deep learning -- AI based industry automation -- Section 3: AI based data management, architecture and framework -- Algorithms and techniques for data management and cloud -- Reference architectures -- Frameworks for integrating IoT, ML and Cloud -- Section 4: Software Portability and Virtual Machine Design -- Virtual Machine designs -- VM design and programming-language/compiler theory concerns -- Section 5: Security for industry 4.0 -- Industry 4.0 -- Artificial intelligence -- Machine Learning -- Signal Processing -- Multimedia -- Big data -- Software Portability -- Virtual Machines -- Conclusion. .
Record Nr. UNINA-9910736004203321
Neustein Amy  
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Foundations of Data Science for Engineering Problem Solving
Foundations of Data Science for Engineering Problem Solving
Autore Mahalle Parikshit Narendra
Pubbl/distr/stampa Singapore : , : Springer Singapore Pte. Limited, , 2021
Descrizione fisica 1 online resource (125 pages)
Altri autori (Persone) ShindeGitanjali Rahul
PisePriya Dudhale
DeshmukhJyoti Yogesh
Collana Studies in Big Data Ser.
Soggetto genere / forma Electronic books.
ISBN 981-16-5160-4
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Contents -- About the Authors -- 1 Introduction to Data Science -- 1.1 What is Data Science? -- 1.2 Evolution with a Need for Data Science -- 1.3 Applications of Data Science -- 1.3.1 Use of Data Science in D-Mart (E-commerce and Retail Management) -- 1.3.2 Narrow Artificial Intelligence (AI) -- 1.3.3 Trustworthy Artificial Intelligence (AI) -- 1.4 Summary -- References -- 2 Data Collection and Preparation -- 2.1 Types of Data -- 2.2 Datasets -- 2.3 Taxonomy of Dataset -- 2.4 Statistical Perspective -- 2.5 Dataset Pre-processing -- 2.6 Data Cleaning -- 2.6.1 Handling Missing Values -- 2.6.2 Removing Noisy Data -- 2.7 Data Transformation -- 2.7.1 Normalization -- 2.7.2 Encoding -- 2.8 Data Reduction -- 2.8.1 Attribute Feature Selection -- 2.8.2 Dimensionality Reduction -- 2.8.3 Numerosity Reduction -- 2.9 Web Scrapping Tools -- 2.10 Summary -- References -- 3 Data Analytics and Learning Techniques -- 3.1 Data Analytics Overview -- 3.2 Machine Learning Approaches -- 3.2.1 Supervised Learning -- 3.2.2 Unsupervised Learning -- 3.2.3 Reinforcement Learning -- 3.3 Deep Learning Approaches -- 3.4 Data Science Roles -- References -- 4 Data Visualization Tools and Data Modelling -- 4.1 Need of Visualization of Data -- 4.1.1 Challenges of Data Visualization -- 4.1.2 Steps of Data Visualization -- 4.2 Visualization Tools -- 4.2.1 Importance of Usage of Tools for Visualization -- 4.2.2 MS Excel -- 4.2.3 Tableau -- 4.2.4 Matplotlib -- 4.2.5 Datawrapper -- 4.2.6 Microsoft PowerBI -- 4.3 Summary -- References -- 5 Data Science in Information, Communication and Technology -- 5.1 Introduction -- 5.2 Motivation -- 5.3 Case Study in Computer Engineering -- 5.3.1 To Choose Fastest Route to Reach Destination -- 5.3.2 To Get Food Recipe Recommendations of Our Interest -- 5.3.3 The Famous Netflix Case Study.
5.3.4 Case Study of Amazon Using Data Science -- 5.3.5 Case Study on KCC (Kisaan Call Center) -- 5.4 Summary -- References -- 6 Data Science in Civil Engineering and Mechanical Engineering -- 6.1 Introduction -- 6.2 Motivation -- 6.3 Case Studies in Civil Engineering -- 6.4 Case Studies in Mechanical Engineering -- 6.5 Summary -- References -- 7 Data Science in Clinical Decision System -- 7.1 Introduction -- 7.2 Motivation -- 7.3 Case Study in Clinical Decision System -- 7.3.1 Preventive Measures for Cardiovascular Disease Using Data Science -- 7.3.2 Case Study on COVID-19 Prediction -- 7.4 Summary -- References -- 8 Conclusions -- 8.1 Conclusions -- 8.2 Open Research Issues -- 8.3 Future Outlook -- References.
Record Nr. UNINA-9910497096203321
Mahalle Parikshit Narendra  
Singapore : , : Springer Singapore Pte. Limited, , 2021
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Predictive analytics for mechanical engineering : a beginner's guide / / by Parikshit N. Mahalle, Pravin P. Hujare, Gitanjali Rahul Shinde
Predictive analytics for mechanical engineering : a beginner's guide / / by Parikshit N. Mahalle, Pravin P. Hujare, Gitanjali Rahul Shinde
Autore Mahalle Parikshit N.
Pubbl/distr/stampa Singapore : , : Springer, , [2023]
Descrizione fisica 1 online resource (107 pages) : illustrations
Disciplina 658.4038028563
Collana SpringerBriefs in computational intelligence
Soggetto topico Computational intelligence
Quantitative research
Mechanical engineering
Internet of things
Computational Intelligence
Data Analysis and Big Data
Mechanical Engineering
Internet of Things
ISBN 981-9948-50-9
9789819948505
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto 1. Introduction to Predictive Analytics -- 2. Data Acquisition and Preparation -- 3. Intelligent Approaches -- 4. Predictive Maintenance -- 5. Predictive Maintenance for Mechanical Design System -- 6. Predictive Maintenance for Manufacturing -- 7. Conclusions.
Record Nr. UNINA-9910741149603321
Mahalle Parikshit N.  
Singapore : , : Springer, , [2023]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui