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91
Background subtraction for online calibration of baseline RSS in RF sensing networks
- IEEE Trans. Mobile Computing
, 2012
"... Radio frequency (RF) sensing networks are a class of wireless sensor networks (WSNs) which use RF signals to accomplish tasks such as passive device-free localization and tracking. The algorithms used for these tasks usually require access to measurements of baseline received signal strength (RSS) o ..."
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Radio frequency (RF) sensing networks are a class of wireless sensor networks (WSNs) which use RF signals to accomplish tasks such as passive device-free localization and tracking. The algorithms used for these tasks usually require access to measurements of baseline received signal strength (RSS) on each link. However, it is often impossible to collect this calibration data (measurements collected during an offline calibration period when the region of interest is empty of targets). We propose adapting background subtraction methods from the field of computer vision to estimate baseline RSS values from measurements taken while the system is online and obstructions may be present. This is done by forming an analogy between the intensity of a background pixel in an image and the baseline RSS value of a WSN link and then translating the concepts of temporal similarity, spatial similarity and spatial ergodicity which underlie specific background subtraction algorithms to WSNs. Using experimental data, we show that these techniques are capable of estimating baseline RSS values with enough accuracy that RF tomographic tracking can be carried out in a variety of different environments without the need for a calibration period. 1
Exploring Indoor White Spaces in Metropolises
"... It is a promising vision to utilize white spaces, i.e., vacant VHF and UHF TV channels, to satisfy skyrocketing wireless data demand in both outdoor and indoor scenarios. While most prior works have focused on exploring outdoor white spaces, the indoor story is largely open for investigation. Motiva ..."
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It is a promising vision to utilize white spaces, i.e., vacant VHF and UHF TV channels, to satisfy skyrocketing wireless data demand in both outdoor and indoor scenarios. While most prior works have focused on exploring outdoor white spaces, the indoor story is largely open for investigation. Motivated by this observation and that 70 % of the spectrum demand comes from indoor environments, we carry out a comprehensive study of exploring indoor white spaces. We first present a large-scale measurement of outdoor and indoor TV spectrum occupancy in 30+ diverse locations in a typical metropolis Hong Kong. Our measurement results confirm abundant white spaces available for exploration in a wide range of areas in metropolises. In particular, more than 50 % and 70 % of the TV spectrum are white spaces in outdoor and indoor scenarios, respectively. While there are substantially more white spaces
Autogait: A mobile platform that accurately estimates the distance walked
- In PerCom 2010
"... Abstract—AutoGait is a mobile platform that autonomously discovers a user’s walking profile and accurately estimates the distance walked. The discovery is made by utilizing the GPS in the user’s mobile device when the user is walking outdoors. This profile can then be used both indoors and outdoors ..."
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Abstract—AutoGait is a mobile platform that autonomously discovers a user’s walking profile and accurately estimates the distance walked. The discovery is made by utilizing the GPS in the user’s mobile device when the user is walking outdoors. This profile can then be used both indoors and outdoors to estimate the distance walked. To model the person’s walking profile, we take advantage of the fact that a linear relationship exists between step frequency and stride length, which is unique to individuals and applies to everyone regardless of age. Autonomous calibration invisible to users allows the system to maintain a high level of accuracy under changing conditions. AutoGait can be integrated into any pedometer or indoor navigation software on handheld devices as long as they are equipped with GPS. The main contribution of this paper is two fold: (1) we propose an auto-calibration method that trains a person’s walking profile by effectively processing noisy GPS readings, and (2) we build a prototype system and validate its performance by performing extensive experiments. Our experimental results confirm that the proposed auto-calibration method can accurately estimate a person’s walking profile and thus significantly reduce the error rate. I.
RescueMe: An Indoor Mobile Augmented-Reality Evacuation System by Personalized Pedometry
"... Abstract—Emergency applications have recently become widely available on modern smartphones. Nearly all of these commercial applications have focused on providing simple accident information in outdoor settings. AR in indoor environments poses unique challenges, due to the unavailability of GPS indo ..."
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Abstract—Emergency applications have recently become widely available on modern smartphones. Nearly all of these commercial applications have focused on providing simple accident information in outdoor settings. AR in indoor environments poses unique challenges, due to the unavailability of GPS indoors and WiFi-based positioning limitations. In this paper, we propose the use of RescueMe, a novel system based on indoor mobile AR applications using personalized pedometry and one that recommends the most optimal, uncrowded exit path to users. We have developed the RescueMe application for use within largescale buildings, with complex paths. We show how RescueMe leverages the sensors on a smartphone, in conjunction with emergency information and daily-based user behavior, to deliver evacuation information in emergency situations. I.
Article Weighted Least Squares Techniques for Improved Received Signal Strength Based Localization
, 2011
"... sensors ..."
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Article A Novel Method for Constructing a WIFI Positioning System with Efficient Manpower
"... www.mdpi.com/journal/sensors ..."
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Article A Fast and Precise Indoor Localization Algorithm Based on an Online Sequential Extreme Learning Machine †
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Indoor Positioning: A Review of Indoor Ultrasonic Positioning systems
"... Abstract — In order to provide location information for indoor applications and context-aware computing, a lot of research is being done since last decade for development of real-time Indoor location system. In this paper, we have investigated indoor location concepts and have focused two major tech ..."
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Abstract — In order to provide location information for indoor applications and context-aware computing, a lot of research is being done since last decade for development of real-time Indoor location system. In this paper, we have investigated indoor location concepts and have focused two major technologies used in many indoor location systems i.e. RF and ultrasonic. An overview of various RF systems that use different RF properties for location estimation has been given. Ultrasonic systems have been reviewed in detail as they provide low cost fine grained location systems. A few well known ultrasonic location systems have been investigated with a comparison of the system based on performance, accuracy and limitations. Keywords-Indoor location system; Radio Frequency;
COIN-GPS: Indoor localization from direct GPS receiving
- In MobiSys
, 2014
"... Due to poor signal strength, multipath e↵ects, and limited on-device computation power, common GPS receivers do not work indoors. This work addresses these challenges by using a steerable, high-gain directional antenna as the front-end of a GPS receiver along with a robust signal processing step and ..."
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Due to poor signal strength, multipath e↵ects, and limited on-device computation power, common GPS receivers do not work indoors. This work addresses these challenges by using a steerable, high-gain directional antenna as the front-end of a GPS receiver along with a robust signal processing step and a novel location estima-tion technique to achieve direct GPS-based indoor localization. By leveraging the computing power of the cloud, we accommodate longer signals for acquisition, and remove the requirement of de-coding timestamps or ephemeris data from GPS signals. We have tested our system in 31 randomly chosen spots inside five single-story, indoor environments such as stores, warehouses and shop-ping centers. Our experiments show that the system is capable of obtaining location fixes from 20 of these spots with a median error of less than 10 m, where all normal GPS receivers fail.
HONEY: A Multimodality Fall Detection and Telecare System
"... ABSTRACT — The increasing cost of finance and healthcare resources is driving healthcare providers to provide home-based telecare instead of institutionalized healthcare. Falling is one of the most common and dangerous accidents for elderly group and a significant factor affecting the living quality ..."
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ABSTRACT — The increasing cost of finance and healthcare resources is driving healthcare providers to provide home-based telecare instead of institutionalized healthcare. Falling is one of the most common and dangerous accidents for elderly group and a significant factor affecting the living quality of the elderly. Many efforts have been put towards providing a robust method to detect falls accurately and timely. To facilitate a reliable, safe and real-time home-based healthcare environment, we propose the HONEY system to detect falls for elderly people in the home telecare environment. The basic idea of HONEY is a three-step detection scheme which consists of multimodality signal sources, including an accelerometer sensor, audio, images and video clips via speech recognition and on-demand video techniques. The magnitude acceleration, corresponding to a user’s movements, triggers fall detection combining speech recognition and
