Journal ArticleDOI
Tool release: gathering 802.11n traces with channel state information
Daniel Halperin,Wenjun Hu,Anmol Sheth,David Wetherall +3 more
- Vol. 41, Iss: 1, pp 53-53
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TLDR
The measurement setup comprises the customized versions of Intel's close-source firmware and open-source iwlwifi wireless driver, userspace tools to enable these measurements, access point functionality for controlling both ends of the link, and Matlab scripts for data analysis.Abstract:
We are pleased to announce the release of a tool that records detailed measurements of the wireless channel along with received 802.11 packet traces. It runs on a commodity 802.11n NIC, and records Channel State Information (CSI) based on the 802.11 standard. Unlike Receive Signal Strength Indicator (RSSI) values, which merely capture the total power received at the listener, the CSI contains information about the channel between sender and receiver at the level of individual data subcarriers, for each pair of transmit and receive antennas.Our toolkit uses the Intel WiFi Link 5300 wireless NIC with 3 antennas. It works on up-to-date Linux operating systems: in our testbed we use Ubuntu 10.04 LTS with the 2.6.36 kernel. The measurement setup comprises our customized versions of Intel's close-source firmware and open-source iwlwifi wireless driver, userspace tools to enable these measurements, access point functionality for controlling both ends of the link, and Matlab (or Octave) scripts for data analysis. We are releasing the binary of the modified firmware, and the source code to all the other components.read more
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Patent
Devices, systems, and methods for detecting gestures using wireless communication signals
TL;DR: The use of wireless communication signals may accordingly make possible gesture recognition in a whole-home environment that may identify gestures performed through walls or other obstacles as mentioned in this paper, which may be used in a home environment.
Journal ArticleDOI
Protecting Water Infrastructure From Cyber and Physical Threats: Using Multimodal Data Fusion and Adaptive Deep Learning to Monitor Critical Systems
Nikolaos Bakalos,Athanasios Voulodimos,Nikolaos Doulamis,Anastasios Doulamis,Avi Ostfeld,Elad Salomons,Juan Caubet,Victor Jimenez,Pau Li +8 more
TL;DR: Critical water infrastructure is susceptible to various types of major attacks, including direct, human-presence assaults and cyberattacks tampering with industrial control system sensors and processes, and requires the exploitation of different data modalities, such as visual surveillance, channel state information (CSI) from Wi-Fi signals for human-Presence detection, and ICS sensor data from the utility.
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Recent advances in RF-based passive device-free localisation for indoor applications
TL;DR: The recent progress of IDFL prioritising on indoor positioning is surveyed, the localisation dimensions are decompose into occupants, space and time, a detailed taxonomy is provided and a comprehensive review of these techniques are evaluated.
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Location-Enabled IoT (LE-IoT): A Survey of Positioning Techniques, Error Sources, and Mitigation
You Li,Yuan Zhuang,Xin Hu,Zhouzheng Gao,Jia Hu,Long Chen,Zhe He,Ling Pei,Kejie Chen,Maosong Wang,Xiaoji Niu,Ruizhi Chen,John Thompson,Fadhel M. Ghannouchi,N. El-Sheimy +14 more
TL;DR: This survey provides comprehensive guidance for peers who are interested in enabling localization ability in the existing IoT systems, using IoT systems for localization, or integrating IoT signals with the existing localization sensors.
Journal ArticleDOI
Device free human activity and fall recognition using WiFi channel state information (CSI)
TL;DR: It is shown that it is possible to characterize activities and/or human body presence with high accuracy and to count the number of people in a room based on the CSI-data, which is a first step towards detecting more complex social behavior and activities.
References
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Proceedings ArticleDOI
Predictable 802.11 packet delivery from wireless channel measurements
TL;DR: It is shown that, for the first time, wireless packet delivery can be accurately predicted for commodity 802.11 NICs from only the channel measurements that they provide, and the rate prediction is as good as the best rate adaptation algorithms for 802.
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