000			03879nam a2200373 i 4500
999			_c398002 _d398002 _x1
001			398002
003			ES-MaUEC
005			20240314174508.0
006			a|||||o|||| 00| 0
007			cr nn 008mamaa
008			221210s2023 sz | o |||| 0|eng d
020			_a9783031151606
024	7		_a10.1007/978-3-031-15160-6 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aTK5105.8857 _b2023 EB
245	0	0	_aIoT Edge Solutions for Cognitive Buildings _cedited by Franco Cicirelli, Antonio Guerrieri, Andrea Vinci, Giandomenico Spezzano
250			_a1st ed 2023
264		1	_aCham _bSpringer International Publishing _c2023
300			_a1 recurso en línea
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	0		_aInternet of Things Technology Communications and Computing _x2199-1081
505	0		_aChapter 1. COGITO: a platform for developing cognitive environments -- Chapter 2. CLOUD, FOG and EDGE COMPUTING for IoT-ENABLED COGNITIVE BUILDINGS -- Chapter 3. Edge caching in IoT smart environments: benefits, challenges and research perspectives towards 6G -- Chapter 4. Needs analysis, protection, and regulation of the rights of individuals and communities for urban and residential comfort in Cognitive Buildings -- Chapter 5. Real case studies towards IoT Based Cognitive Environments -- Chapter 6. Audio analysis for enhancing security in cognitive environments through AI on the Edge -- Chapter 7. Aggregate Programming for customized building management and users preference implementation -- Chapter 8. IoT control based solar shadings: advanced operating strategy to optimize energy savings and visual comfort -- Chapter 9. Room occupancy prediction leveraging LSTM - An approach for cognitive and self-adapting buildings -- Chapter 10. Edge Intelligence against COVID-19: a Smart University Campus case study -- Chapter 11. Structural Health Monitoring in Cognitive Buildings -- Chapter 12. Development of Indoor Smart Environments leveraging the Internet of Things and Artificial Intelligence: a case study -- Chapter 13. Human-centered Reinforcement Learning for Lighting and Blind Control in Cognitive Buildings -- Chapter 14. Intelligent Load Scheduling in Cognitive Buildings: A Use Case -- Chapter 15. Cognitive Systems for Energy Efficiency and Thermal Comfort in Smart Buildings.
520			_aThis book outlines the promise of the field of the Cognitive Internet of Things when it is applied to cognitive buildings. After an introduction, the authors discuss the goals of cognitive buildings such as operation in a more efficient, flexible, interactive, intuitive, and sustainable way. They go on to outline the benefits that these technologies promise to building owners, occupants, and their environments that range from reducing energy consumption and carbon footprint to promoting health, well-being, and productivity. The authors outline technologies that provide buildings and equipment with the ability to collect, aggregate, and analyze data and how this information can be collected by sensors and related to internal conditions and settings, energy consumption, user requests, and preferences to maintain comfort and save energy. This book is of interest to practitioners, researchers, students, and professors in IoT and smart cities.
988			_aSpringer_Computer_2023
650		7	_2embne _9483083 _aInternet de los objetos
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-15160-6 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b01/2024 _dz _eb _zSI