RSSI-Based Localizations
CRC Press (Verlag)
978-1-041-12421-4 (ISBN)
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An important coverage in the book is the integration of machine learning (ML) with RSSI data. The authors cover supervised, unsupervised, and deep learning techniques, focusing on enhancing accuracy, scalability, and adaptability. The reader learns how to apply ML techniques and gain further insight into the advanced applications of RSSI data. Such knowledge allows for the development of more accurate and scalable systems, creation of intelligent IoT systems. An important hospital case is included to study RSSI-based monitoring in healthcare. It features a real-world example which details the implementation, challenges, and results of the case study. The practical insights demonstrate the potential benefits and challenges of RSSI-based healthcare solutions and inspires the development of innovative solutions in healthcare and potentially other domains, integrating machine learning capabilities.
The readership for this book is graduate students in wireless sensor network and IoT courses, professionals such as developers and researchers developing smart communications in factories, hospitals, buildings.
Nattha Jindapetch obtained her PhD from the University of Tokyo on advanced Science and technology. She is currently an Associate Professor with the Department of Electrical Engineering at Prince of Songkla University. Her research interests include FPGAs, embedded systems, and sensor networks. Thradon Wattananavin received the B.Eng. degree and the M.Eng. degree in Electrical Engineering from Prince of Songkla University in 2009 and 2014, respectively. He now is a lecturer at the Faculty of Industrial Technology, Nakhon Si Thammarat Rajabhat University, Thailand. Currently, he is also studying for a PhD in Electrical Engineering at the Department of Electrical and Biomedical Engineering, Faculty of Engineering, Prince of Songkla University, where his research topic focuses on received signal strength-based indoor localization and human activity recognition. His research interests include wireless sensor networks, RSSI-based localization, medium access control (MAC) protocols, wireless network communications, fingerprinting, and machine learning. Kittikhun Thongpull is Director of Next-generation Innovations in Connected and Digital Technology Research at the Prince of Songkla University. He received his PhD from the Kaiserslautern University of Technology in Germany. Apidet Booranawong teaches electrical engineering, at the Prince of Songkla University. His research is in the areas of Wireless Sensor Networks, Wireless Sensor and Actuator Networks and Routing Algorithms.
1 RSSI Theory: An Overview 2 Localization Systems and Communication Technologies 3 RSSI accuracy and compensation techniques RSSI based localization and applications 5 RSSI based device-free detection and applications 6 Machine Learning for High-Precision Indoor Localization
| Erscheint lt. Verlag | 15.5.2026 |
|---|---|
| Zusatzinfo | 36 Tables, black and white; 90 Line drawings, black and white; 90 Illustrations, black and white |
| Verlagsort | London |
| Sprache | englisch |
| Maße | 156 x 234 mm |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| Technik ► Nachrichtentechnik | |
| ISBN-10 | 1-041-12421-X / 104112421X |
| ISBN-13 | 978-1-041-12421-4 / 9781041124214 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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