| |
|
|
|
|
|
|
|
|
1. |
Record Nr. |
UNINA9910899898903321 |
|
|
Autore |
Pradhan Biswajeet |
|
|
Titolo |
IoT Sensors, ML, AI and XAI: Empowering A Smarter World / / edited by Biswajeet Pradhan, Subhas Mukhopadhyay |
|
|
|
|
|
|
|
Pubbl/distr/stampa |
|
|
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
|
|
|
|
|
|
|
ISBN |
|
|
|
|
|
|
|
|
Edizione |
[1st ed. 2024.] |
|
|
|
|
|
Descrizione fisica |
|
1 online resource (479 pages) |
|
|
|
|
|
|
Collana |
|
Smart Sensors, Measurement and Instrumentation, , 2194-8410 ; ; 50 |
|
|
|
|
|
|
Altri autori (Persone) |
|
|
|
|
|
|
Disciplina |
|
|
|
|
|
|
Soggetti |
|
Computational intelligence |
Internet of things |
Materials |
Detectors |
Mechatronics |
Computational Intelligence |
Internet of Things |
Sensors and biosensors |
|
|
|
|
|
|
|
|
Lingua di pubblicazione |
|
|
|
|
|
|
Formato |
Materiale a stampa |
|
|
|
|
|
Livello bibliografico |
Monografia |
|
|
|
|
|
Nota di contenuto |
|
Sensors ML and AI for Real World Applications -- Flying IoT Sensor Fusion Performance Analysis for UAV Applications in Indoor Spaces -- Machine Learning Empowered IoT Devices Analysis of Indoor and Outdoor Temperature and Health Risks -- Identification of IoT devices through Machine Learning and hardware fingerprints based on clock skew. |
|
|
|
|
|
|
|
|
Sommario/riassunto |
|
This book uncovers and presents various real-life applications in the areas of transportation, smart cities, manufacturing, agriculture, disaster management, finance, health care and in other areas by using cutting-edge advanced Machine Learning (ML) techniques such as Deep Learning and Explainable AI (XAI) models using IoT sensor data. The book provides various examples of analyzing large amounts of data, detecting patterns, and making predictions in real-time applications and detailed case studies with practical solutions using various state- |
|
|
|
|
|
|
|
|
|
|
of-the-art machine learning and IoT sensor data and all these aspects will benefit the stakeholders. The book is useful for academics, researchers, upper-undergraduate, master and Ph.D. students, engineers and practitioners in sensor/IoT and AI/ML technologies, methods, applications, and related areas, and it also offers valuable insights by suggesting future research directions and providing recommendations within the fields of AI and IoT. |
|
|
|
|
|
| |