63,061 research outputs found
Probabilistic Human Mobility Model in Indoor Environment
Understanding human mobility is important for the development of intelligent
mobile service robots as it can provide prior knowledge and predictions of
human distribution for robot-assisted activities. In this paper, we propose a
probabilistic method to model human motion behaviors which is determined by
both internal and external factors in an indoor environment. While the internal
factors are represented by the individual preferences, aims and interests, the
external factors are indicated by the stimulation of the environment. We model
the randomness of human macro-level movement, e.g., the probability of visiting
a specific place and staying time, under the Bayesian framework, considering
the influence of both internal and external variables. We use two case studies
in a shopping mall and in a college student dorm building to show the
effectiveness of our proposed probabilistic human mobility model. Real
surveillance camera data are used to validate the proposed model together with
survey data in the case study of student dorm.Comment: 8 pages, 9 figures, International Joint Conference on Neural Networks
(IJCNN) 201
GLOBAL CHANGE REACTIVE BACKGROUND SUBTRACTION
Background subtraction is the technique of segmenting moving foreground objects from stationary or dynamic background scenes. Background subtraction is a critical step in many computer vision applications including video surveillance, tracking, gesture recognition etc. This thesis addresses the challenges associated with the background subtraction systems due to the sudden illumination changes happening in an indoor environment. Most of the existing techniques adapt to gradual illumination changes, but fail to cope with the sudden illumination changes. Here, we introduce a Global change reactive background subtraction to model these changes as a regression function of spatial image coordinates. The regression model is learned from highly probable background regions and the background model is compensated for the illumination changes by the model parameters estimated. Experiments were performed in the indoor environment to show the effectiveness of our approach in modeling the sudden illumination changes by a higher order regression polynomial. The results of non-linear SVM regression were also presented to show the robustness of our regression model
A novel wideband dynamic directional indoor channel model based on a Markov process
This document is made available in accordance with publisher policies. Please cite only the published version using the reference above. Full terms of use are available
5G 3GPP-like Channel Models for Outdoor Urban Microcellular and Macrocellular Environments
For the development of new 5G systems to operate in bands up to 100 GHz,
there is a need for accurate radio propagation models at these bands that
currently are not addressed by existing channel models developed for bands
below 6 GHz. This document presents a preliminary overview of 5G channel models
for bands up to 100 GHz. These have been derived based on extensive measurement
and ray tracing results across a multitude of frequencies from 6 GHz to 100
GHz, and this document describes an initial 3D channel model which includes: 1)
typical deployment scenarios for urban microcells (UMi) and urban macrocells
(UMa), and 2) a baseline model for incorporating path loss, shadow fading, line
of sight probability, penetration and blockage models for the typical
scenarios. Various processing methodologies such as clustering and antenna
decoupling algorithms are also presented.Comment: To be published in 2016 IEEE 83rd Vehicular Technology Conference
Spring (VTC 2016-Spring), Nanjing, China, May 201
AROMA: Automatic Generation of Radio Maps for Localization Systems
WLAN localization has become an active research field recently. Due to the
wide WLAN deployment, WLAN localization provides ubiquitous coverage and adds
to the value of the wireless network by providing the location of its users
without using any additional hardware. However, WLAN localization systems
usually require constructing a radio map, which is a major barrier of WLAN
localization systems' deployment. The radio map stores information about the
signal strength from different signal strength streams at selected locations in
the site of interest. Typical construction of a radio map involves measurements
and calibrations making it a tedious and time-consuming operation. In this
paper, we present the AROMA system that automatically constructs accurate
active and passive radio maps for both device-based and device-free WLAN
localization systems. AROMA has three main goals: high accuracy, low
computational requirements, and minimum user overhead. To achieve high
accuracy, AROMA uses 3D ray tracing enhanced with the uniform theory of
diffraction (UTD) to model the electric field behavior and the human shadowing
effect. AROMA also automates a number of routine tasks, such as importing
building models and automatic sampling of the area of interest, to reduce the
user's overhead. Finally, AROMA uses a number of optimization techniques to
reduce the computational requirements. We present our system architecture and
describe the details of its different components that allow AROMA to achieve
its goals. We evaluate AROMA in two different testbeds. Our experiments show
that the predicted signal strength differs from the measurements by a maximum
average absolute error of 3.18 dBm achieving a maximum localization error of
2.44m for both the device-based and device-free cases.Comment: 14 pages, 17 figure
Effect of pedestrian movement on MIMO-OFDM channel capacity in an indoor environment
Effects of pedestrian movement on multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) channel capacity have been investigated using experiment and simulation. The experiment was conducted at 5.2 GHz by a MIMO-OFDM packet transmission demonstrator using four transmitters and four receivers built in-house. Geometric optics based ray tracing technique was used to simulate the experimental scenarios. Changes in the channel capacity dynamic range have been analysed for different number of pedestrian (0-3) and antennas (2-4). Measurement and simulation results show that the dynamic range increases with the number of pedestrian and the number of antennas on the transmitter and receiver array
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