Journal ArticleDOI
Enhanced Fingerprinting and Trajectory Prediction for IoT Localization in Smart Buildings
TLDR
A novel localization approach that utilizes the neighbor relative received signal strength to build the fingerprint database and adopts a Markov-chain prediction model to assist positioning is proposed.Abstract:
Location service is one of the primary services in smart automated systems of Internet of Things (IoT). For various location-based services, accurate localization has become a key issue. Recently, research on IoT localization systems for smart buildings has been attracting increasing attention. In this paper, we propose a novel localization approach that utilizes the neighbor relative received signal strength to build the fingerprint database and adopts a Markov-chain prediction model to assist positioning. The approach is called the novel localization method (LNM) in short. In the proposed LNM scheme, the history data of the pedestrian’s locations are analyzed to further lower the unpredictable signal fluctuations in a smart building environment, meanwhile enabling calibration-free positioning for various devices. The performance evaluation conducted in a realistic environment shows that the presented method demonstrates superior localization performance compared with well-known existing schemes, especially when the problems of device heterogeneity and WiFi signals fluctuation exist.read more
Citations
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Journal ArticleDOI
Disease Prediction by Machine Learning Over Big Data From Healthcare Communities
TL;DR: This paper streamline machine learning algorithms for effective prediction of chronic disease outbreak in disease-frequent communities by proposing a new convolutional neural network (CNN)-based multimodal disease risk prediction algorithm using structured and unstructured data from hospital.
Journal ArticleDOI
Evaluating Critical Security Issues of the IoT World: Present and Future Challenges
TL;DR: This paper tries to bring order on the IoT security panorama providing a taxonomic analysis from the perspective of the three main key layers of the IoT system model: 1) perception; 2) transportation; and 3) application levels.
Journal ArticleDOI
Efficient IoT-based sensor BIG Data collection–processing and analysis in smart buildings
TL;DR: The proposed solutions for collecting and managing sensors’ data in a smart building could lead us in an energy efficient smart building, and thus in a Green Smart Building.
Journal ArticleDOI
Smart Clothing: Connecting Human with Clouds and Big Data for Sustainable Health Monitoring
TL;DR: Typical applications powered by smart clothing and big data clouds are presented, such as medical emergency response, emotion care, disease diagnosis, and real-time tactile interaction.
Journal ArticleDOI
Robustness, Security and Privacy in Location-Based Services for Future IoT: A Survey
Liang Chen,Sarang Thombre,Kimmo Järvinen,Elena Simona Lohan,Anette Alen-Savikko,Helena Leppäkoski,M. Zahidul H. Bhuiyan,Shakila Bu-Pasha,Giorgia Ferrara,Salomon Honkala,Jenna Lindqvist,Laura Ruotsalainen,Päivi Korpisaari,Heidi Kuusniemi +13 more
TL;DR: This survey paper addresses a broad range of security and privacy aspects in IoT-based positioning and localization from both technical and legal points of view and aims to give insight and recommendations for future IoT systems providing more robust, secure, and privacy-preserving location-based services.
References
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Journal ArticleDOI
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Proceedings ArticleDOI
RADAR: an in-building RF-based user location and tracking system
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Book
Understanding GPS : principles and applications
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Proceedings ArticleDOI
The Cricket location-support system
TL;DR: The randomized algorithm used by beacons to transmit information, the use of concurrent radio and ultrasonic signals to infer distance, the listener inference algorithms to overcome multipath and interference, and practical beacon configuration and positioning techniques that improve accuracy are described.
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