Physical Sciences and Mathematics Commons^™

Interactionless Calendar-Based Training For 802.11 Localization, Mark Chang, Andrew J. Barry, Noah L. Tye

Mark L. Chang

This paper presents our work in solving one of the weakest links in 802.11-based indoor-localization: the training of ground-truth received signal strength data. While crowdsourcing this information has been demonstrated to be a viable alternative to the time consuming and accuracy-limited process of manual training, one of the chief drawbacks is the rate at which a system can be trained. We demonstrate an approach that utilizes users' calendar and appointment information to perform interactionless training of an 802.11-based indoor localization system. Our system automatically determines if a user attended a calendar event, resulting in accuracy comparable to our previously published …

Pandaa: Physical Arrangement Detection Of Networked Devices Through Ambient-Sound Awareness, Zheng Sun, Aveek Purohit, Kaifei Chen, Shijia Pan, Trevor Pering, Pei Zhang

Zheng Sun

Future ubiquitous home environments can contain 10s or 100s of devices. Ubiquitous services running on these devices (i.e. localizing users, routing, security algorithms) will commonly require an accurate location of each device. In order to obtain these locations, existing techniques require either a manual survey, active sound sources, or estimation using wireless radios. These techniques, however, need additional hardware capabilities and are intrusive to the user. Non-intrusive, automatic localization of ubiquitous computing devices in the home has the potential to greatly facilitate device deployments.

This paper presents the PANDAA system, a zero-configuration spatial localization system for networked devices based on …

Pandaa: Physical Arrangement Detection Of Networked Devices Through Ambient-Sound Awareness, Zheng Sun, Aveek Purohit, Kaifei Chen, Shijia Pan, Trevor Pering, Pei Zhang

Aveek Purohit

Future ubiquitous home environments can contain 10s or 100s of devices. Ubiquitous services running on these devices (i.e. localizing users, routing, security algorithms) will commonly require an accurate location of each device. In order to obtain these locations, existing techniques require either a manual survey, active sound sources, or estimation using wireless radios. These techniques, however, need additional hardware capabilities and are intrusive to the user. Non-intrusive, automatic localization of ubiquitous computing devices in the home has the potential to greatly facilitate device deployments.

This paper presents the PANDAA system, a zero-configuration spatial localization system for networked devices based on …

Pandaa: A Physical Arrangement Detection Technique For Networked Devices Through Ambient-Sound Awareness, Zheng Sun, Aveek Purohit, Philippe De Wagter, Irina Brinster, Chorom Hamm, Pei Zhang

Zheng Sun

This demo presents PANDAA, a zero-configuration automatic spatial localization technique for networked devices based on ambient sound sensing. We will demonstrate that after initial placement of the devices, ambient sounds, such as human speech, music, footsteps, finger snaps, hand claps, or coughs and sneezes, can be used to autonomously resolve the spatial relative arrangement of devices, such as mobile phones, using trigonometric bounds and successive approximation.

Correlations Due To Localization In Quantum Eigenfunctions Of Disordered Microwave Cavities, Prabhakar Pradhan, S. Sridhar

Srinivas Sridhar

Non-universal correlations due to localization are observed in statistical properties of experimental eigenfunctions of quantum chaotic and disordered microwave cavities. Varying energy E and mean free path ℓ enable us to experimentally tune from localized to delocalized states. Large level-to-level Inverse Participation Ratio (IPR I₂) fluctuations are observed for the disordered billiards, whose distribution is strongly asymmetric about 〈I₂〉. The density auto-correlations of eigenfunctions are shown to decay exponentially and the decay lengths are experimentally determined. All the results are quantitatively consistent with calculations based upon nonlinear α− models.

Improved Vehicle Based Multibeam Bathymetry Using Sub-Maps And Slam, Christopher Roman, Hanumant Singh

Christopher N. Roman

This paper presents an algorithm to improve sub-sea acoustic multibeam bottom mapping based on the simultaneous mapping and localization (SLAM) methodology. Multibeam bathymetry from underwater water vehicles can yield valuable large scale terrain maps of the sea door, but the overall accuracy of these maps is typically limited by the accuracy of the vehicle position estimates. The solution presented here uses small bathymetric patches created over short time scales in a sub-mapping context. These patches are registered with respect to one another and assembled in a single coordinate frame to produce a more accurate terrain estimate and provide improved renavigation …