The book covers the integration of Internet of Things (IoT) and Artificial Intelligence (AI) to tackle applications in smart healthcare. The authors discuss efficient means to collect, monitor, control, optimize, model, and predict healthcare data using AI and IoT. The book presents the many advantages and improvements in the smart healthcare field, in which ubiquitous computing and traditional computational methods alone are often inadequate. AI techniques are presented that play a crucial role in dealing with large amounts of heterogeneous, multi-scale and multi-modal data coming from IoT infrastructures. The book is intended to cover how the fusion of IoT and AI allows the design of models, methodologies, algorithms, evaluation benchmarks, and tools can address challenging problems related to health informatics, healthcare, and wellbeing.
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The book covers the integration of Internet of Things (IoT) and Artificial Intelligence (AI) to tackle applications in smart healthcare.
1. Lower-Gait Tracking Application Using Smartphones and Tablets.- 2. One-class classification approach in accelerometer based remote monitoring of physical activities for healthcare applications.- 3. Detecting and monitoring behavioural patterns in individuals with cognitive disorders in the home environment with partial annotations.- 4. Towards On-device Weight Monitoring from Selfie Face Images Using Smartphones.- 5. Convergence between IoT and AI for Smart Health and Predictive Medicine.- 6. An Artificial Intelligence and Internet of Things Platform for Healthcare and Industrial Applications.- 7. Methods in Digital Mental Health: Smartphone-based Assessment and Intervention for Stress, Anxiety and Depression .- 8. AI for the detection of the Diabetic Retinopathy.- 9. Enhancing EEG-based Emotion Recognition with Fast Online Instance Transfer.- 10. Using Association Rules to mine Actionable Knowledge from Internet of Medical Thinks data.
Les mer
The book covers the integration of Internet of Things (IoT) and Artificial Intelligence (AI) to tackle applications in smart healthcare. The authors discuss efficient means to collect, monitor, control, optimize, model, and predict healthcare data using AI and IoT. The book presents the many advantages and improvements in the smart healthcare field, in which ubiquitous computing and traditional computational methods alone are often inadequate. AI techniques are presented that play a crucial role in dealing with large amounts of heterogeneous, multi-scale and multi-modal data coming from IoT infrastructures. The book is intended to cover how the fusion of IoT and AI allows the design of models, methodologies, algorithms, evaluation benchmarks, and tools can address challenging problems related to health informatics, healthcare, and wellbeing.
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Covers the integration of Internet of Things (IoT) and Artificial Intelligence (AI) in the healthcare industry Shows how to efficiently collect, monitor, control, optimization, model and predict healthcare using IoT and AI Includes innovative and advanced methodological, theoretical, and mathematical modelling to address
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Produktdetaljer
ISBN
9783030911836
Publisert
2023-02-11
Utgiver
Vendor
Springer Nature Switzerland AG
Høyde
235 mm
Bredde
155 mm
Aldersnivå
Research, P, 06
Språk
Product language
Engelsk
Format
Product format
Heftet
Om bidragsyterne
Carmela Comito is a Research Scientist at the Institute of High Performance Computing and Networking of the Italian National Research Council (ICAR-CNR), Italy. She received her Master’s degree in Computer Engineering and her Ph.D. in Systems and Computer Engineering from the University of Calabria, Italy. In 2006 she was a visiting researcher at the School of Computer Science of the University of Manchester, UK, and in 2017 she was a visiting researcher at LIRMM, University of Montpellier, France. She is adjunct professor at University of Calabria. She co-authored over 80 papers in international journals, conference proceedings, and edited volumes. She served as a chair, program committee member and reviewer of several international conferences. Her research interests include artificial intelligence, big data analysis and mining, mobility mining, social network data analysis and mining, health informatics. She was the organizer and program chair of the International Workshop on SocialMedia Analytics for Healthcare (SMA4H), held in conjunction with Web Intelligence Conference (WI) in 2018, 2019 and 2020. She was the organizer and program chair of the special session “Machine Learning in Health” at the IEEE International Conference on Machine Learning and Applications (IEEE ICMLA) in 2019 and 2020. She was the organizer and program chair of the First International Workshop on Artificial Intelligence for HEaLth, PersonaLized MedIcine aNd WEllbeing (HELPLINE), held in conjunction with the 24th European Conference on Artificial Intelligence (ECAI) 2020.Agostino Forestiero is researcher at the Institute for High Performance Computing and Networking of National Research Council of Italy, (ICAR-CNR), Cosenza, since 2010. He received his Ph.D. in Computer Engineering (2007) and the Master Degree in Computer Engineering (2002) from the University of Calabria. He published more than 80 scientific papers on international conferences and journalsamong which IEEE/ACM TON, IEEE TEVC, IEEE TGCN, Information Sciences, FGCS and ACM TAAS. His research interests include Artificial Intelligence, Social mining, eHealth, Cloud Computing, Distributed systems, Swarm Intelligence, Internet of Things, Multiagent system and Cyber security. He has served as a Program Committee Member several conferences/workshops among which ICMLA 2020, HELPLINE 2020, ICAART 2020, ICMLA 2019, ASONAM 2019, SMA4H 2019, Web Intelligence 2019, ICAART 2019, Web Intelligence 2018, ICAART 2018, SMA4H 2018, ICNSC 2017, IoTGC 2017, ICAART 2017, ICAART 2016, IEEE Cluster 2015, Euro-Par 2014, Euro-Par 2013, Euro-PAR 2010, and international journal, among which IEEE TPDS, IEEE/ACM TON, IEEE TC, IEEE TEVC, ACM TAAS, and several Elsevier and Springer journals. He is co-founder of the company eco4cloud srl, recognized as a spin-off of University of Calabria and CNR and he filled 6 international patents.
Ester Zumpano received her Ph.D. in computerscience at the University of Calabria in 2003. From 2003 to 2006 she was an assistant professor at the University of Calabria. She has been an associate professor at University of Calabria since 2006. Her research interests include Inconsistent Databases, Integration Techniques, P2P Systems, and Logic Programs with Preferences. She has published regularly in international journals and at international conferences.