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We show with various experiments that we can reliably detect WiFi-enabled mobile phones from the air at distances up to 200 m. By using a custom mobile application that triggers WiFi scanning with the display off, we can simultaneously extend battery life and increase WiFi scanning frequency, compared to keeping the phone in the default scanning mode.
Open accessProceedings ArticleDOI
11 Mar 2019
29 Citations
Our solution, WiWear, has two key innovations: 1) beamforming WiFi transmissions to significantly boost the energy that a receiver can harvest ~2-3 meters away, and 2) smart zero-energy, triggering of inertial sensing, that allows intelligent duty-cycled operation of devices whose transient power consumption far exceeds what can be instantaneously harvested.
For home and work environments, aggressive WiFi scans can significantly improve the speed at which mobile nodes join the WiFi network.
Our methods enable the application of signal to interference and noise (SINR) based scheduling algorithms to WiFi networks resulting in tremendous increase in throughput and QoS/fairness.
Proceedings ArticleDOI
Sihui Han, Kang G. Shin 
01 May 2017
18 Citations
It enhances both WiFi signal and low-power IoT devices without changing their configurations or network protocols.
Proceedings ArticleDOI
17 Aug 2015
418 Citations
Specifically, we show that it is possible to design devices and WiFi APs such that the WiFi AP in the process of transmitting data to normal WiFi clients can decode backscatter signals which the devices generate by modulating information on to the ambient WiFi transmission.
Our results supported that the WiFi-aided MM algorithm provided more reliable solutions than both WiFi and MM in the areas that have poor WiFi signal distribution or indistinctive magnetic-gradient features.
Open accessProceedings ArticleDOI
Shu Liu, Aaron Striegel 
13 Aug 2012
31 Citations
We believe the root cause of lesser WiFi utilization can be traced to the WiFi being optimized for laptop WiFi reception rather than the more constrained smartphone WiFi reception.
However, the multi-path fading of WiFi signals causes time-varying received signal strengths of WiFi signals, which leads to poor accuracy of WiFi localization.
The proposed algorithm provided more reliable solutions than both PDR/WiFi and PDR/MM, especially in areas with poor WiFi signal distribution or indistinctive magnetic features.