3,518 research outputs found
Group-In: Group Inference from Wireless Traces of Mobile Devices
This paper proposes Group-In, a wireless scanning system to detect static or
mobile people groups in indoor or outdoor environments. Group-In collects only
wireless traces from the Bluetooth-enabled mobile devices for group inference.
The key problem addressed in this work is to detect not only static groups but
also moving groups with a multi-phased approach based only noisy wireless
Received Signal Strength Indicator (RSSIs) observed by multiple wireless
scanners without localization support. We propose new centralized and
decentralized schemes to process the sparse and noisy wireless data, and
leverage graph-based clustering techniques for group detection from short-term
and long-term aspects. Group-In provides two outcomes: 1) group detection in
short time intervals such as two minutes and 2) long-term linkages such as a
month. To verify the performance, we conduct two experimental studies. One
consists of 27 controlled scenarios in the lab environments. The other is a
real-world scenario where we place Bluetooth scanners in an office environment,
and employees carry beacons for more than one month. Both the controlled and
real-world experiments result in high accuracy group detection in short time
intervals and sampling liberties in terms of the Jaccard index and pairwise
similarity coefficient.Comment: This work has been funded by the EU Horizon 2020 Programme under
Grant Agreements No. 731993 AUTOPILOT and No.871249 LOCUS projects. The
content of this paper does not reflect the official opinion of the EU.
Responsibility for the information and views expressed therein lies entirely
with the authors. Proc. of ACM/IEEE IPSN'20, 202
RFID Localisation For Internet Of Things Smart Homes: A Survey
The Internet of Things (IoT) enables numerous business opportunities in
fields as diverse as e-health, smart cities, smart homes, among many others.
The IoT incorporates multiple long-range, short-range, and personal area
wireless networks and technologies into the designs of IoT applications.
Localisation in indoor positioning systems plays an important role in the IoT.
Location Based IoT applications range from tracking objects and people in
real-time, assets management, agriculture, assisted monitoring technologies for
healthcare, and smart homes, to name a few. Radio Frequency based systems for
indoor positioning such as Radio Frequency Identification (RFID) is a key
enabler technology for the IoT due to its costeffective, high readability
rates, automatic identification and, importantly, its energy efficiency
characteristic. This paper reviews the state-of-the-art RFID technologies in
IoT Smart Homes applications. It presents several comparable studies of RFID
based projects in smart homes and discusses the applications, techniques,
algorithms, and challenges of adopting RFID technologies in IoT smart home
systems.Comment: 18 pages, 2 figures, 3 table
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