Ultra-wideband cognitive interrogator network for indoor location tracking - part 1: system architecture and network performance analysis

We explore the potential application of cognitive interrogator network (CIN) in remote monitoring of mobile subjects in domestic environments, where the ultra-wideband radio frequency identification (UWB-RFID) technique is considered for accurate source localization. We first present the CIN architecture in which the central base station (BS) continuously and intelligently customizes the illumination modes of the distributed transceivers in response to the systempsilas changing knowledge of the channel conditions and subject movements. Subsequently, the analytical results of the locating probability and time-of-arrival (TOA) estimation uncertainty for a large-scale CIN with randomly distributed interrogators are derived based upon the implemented cognitive intelligences. Finally, numerical examples are used to demonstrate the key effects of the proposed cognitions on the system performance

Disposable maps : ad hoc location sharing

The gathering of people in everyday life is intertwined with travelling to negotiated locations. As a result, mobile phones are often used to rearrange meetings when one or more participants are late or cannot make it on time. Our research is based on the hypothesis that the provision of location data can enhance the experience of people who are meeting each other in different locations. This paper presents work-in-progress on a novel approach to share one’s location data in real-time which is visualised on a web-based map in a privacy conscious way. Disposable Maps allows users to select contacts from their phone’s address book who then receive up-to-date location data. The utilisation of peer-to-peer notifications and the application of unique URLs for location storage and presentation enable location sharing whilst ensuring users’ location privacy. In contrast to other location sharing services like Google Latitude, Disposable Maps enables ad hoc location sharing to actively selected location receivers for a fixed period of time in a specific given situation. We present first insights from an initial application user test and show future work on the approach of disposable information allocation.

adaptive location update mechanism for network-constrained moving objects in changeful traffic conditions

Natl Chiao Tung Univ, Dept Comp Sci

Range-based Weighted-likelihood Particle Filter for RSS-based Indoor Tracking

Attractive business cases in various application fields contribute to the sustained long-term interest in indoor localization and tracking by the research community. Location tracking is generally treated as a dynamic state estimation problem, consisting of two steps: (i) location estimation through measurement, and (ii) location prediction. For the estimation step, one of the most efficient and low-cost solutions is Received Signal Strength (RSS)-based ranging. However, various challenges - unrealistic propagation model, non-line of sight (NLOS), and multipath propagation - are yet to be addressed. Particle filters are a popular choice for dealing with the inherent non-linearities in both location measurements and motion dynamics. While such filters have been successfully applied to accurate, time-based ranging measurements, dealing with the more error-prone RSS based ranging is still challenging. In this work, we address the above issues with a novel, weighted likelihood, bootstrap particle filter for tracking via RSS-based ranging. Our filter weights the individual likelihoods from different anchor nodes exponentially, according to the ranging estimation. We also employ an improved propagation model for more accurate RSS-based ranging, which we suggested in recent work. We implemented and tested our algorithm in a passive localization system with IEEE 802.15.4 signals, showing that our proposed solution largely outperforms a traditional bootstrap particle filter.

WHERE2 location aided communications

This paper presents an overview of preliminary results of investigations within the WHERE2 Project on identifying promising avenues for location aided enhancements to wireless communication systems. The wide ranging contributions are organized according to the following targeted systems: cellular networks, mobile ad hoc networks (MANETs) and cognitive radio. Location based approaches are found to alleviate significant signaling overhead in various forms of modern communication paradigms that are very information hungry in terms of channel state information at the transmitter(s). And this at a reasonable cost given the ubiquitous availability of location information in recent wireless standards or smart phones. Location tracking furthermore opens the new perspective of slow fading prediction.

Intrusion warning and assessment method for site safety enhancement

Intrusion (unauthorized stepping-into/staying-in a hazardous area), as a common type of near-miss, is the prime cause of the majority of incidents on construction sites including fall from heights, and striking against or being struck by moving objects. Accidents often occur because workers take shortcuts moving about the site without fully perceiving the potential dangers. A number of researches have been devoted to developing methods to prevent such behaviors mainly based on the theory of Behavior-Based Safety (BBS), which aims to cultivate safety behaviors among workers in accordance with safety regulations. In current BBS practice, trained observers and safety supervisors are responsible for safety behavior inspections following safety plans and operation regulations. The observation process is time-consuming and its effectiveness depends largely on the observer’s safety knowledge and experience, which often results in omissions or bias. This paper presents a reformed safety behavior modification approach by integrating a location-based technology with BBS. Firstly, a detailed background is provided, covering current intrusion problems on site, existing use of BBS for behavior improvement, difficulties in achieving widespread adoption and potential technologies for location tracking and in-time feedback. Then, a conceptual framework of positioning technology-enhanced BBS is developed, followed by details of the corresponding on-line supporting system, Real Time Location System (RTLS) and Virtual Construction System (VCS). The application of the system is then demonstrated and tested in a construction site in Hong Kong. Final comments are made concerning further research direction and prospects for wider adoption.

A framework for experimental determination of localised vertical pedestrian forces on full-scale structures using wireless attitude and heading reference systems

A major weakness among loading models for pedestrians walking on flexible structures proposed in recent years is the various uncorroborated assumptions made in their development. This applies to spatio-temporal characteristics of pedestrian loading and the nature of multi-object interactions. To alleviate this problem, a framework for the determination of localised pedestrian forces on full-scale structures is presented using a wireless attitude and heading reference systems (AHRS). An AHRS comprises a triad of tri-axial accelerometers, gyroscopes and magnetometers managed by a dedicated data processing unit, allowing motion in three-dimensional space to be reconstructed. A pedestrian loading model based on a single point inertial measurement from an AHRS is derived and shown to perform well against benchmark data collected on an instrumented treadmill. Unlike other models, the current model does not take any predefined form nor does it require any extrapolations as to the timing and amplitude of pedestrian loading. In order to assess correctly the influence of the moving pedestrian on behaviour of a structure, an algorithm for tracking the point of application of pedestrian force is developed based on data from a single AHRS attached to a foot. A set of controlled walking tests with a single pedestrian is conducted on a real footbridge for validation purposes. A remarkably good match between the measured and simulated bridge response is found, indeed confirming applicability of the proposed framework.

A camera based digit location and recognition system for garment tracking

Garment information tracking is required for clean room garment management. In this paper, we present a camera-based robust system with implementation of Optical Character Reconition (OCR) techniques to fulfill garment label recognition. In the system, a camera is used for image capturing; an adaptive thresholding algorithm is employed to generate binary images; Connected Component Labelling (CCL) is then adopted for object detection in the binary image as a part of finding the ROI (Region of Interest); Artificial Neural Networks (ANNs) with the BP (Back Propagation) learning algorithm are used for digit recognition; and finally the system is verified by a system database. The system has been tested. The results show that it is capable of coping with variance of lighting, digit twisting, background complexity, and font orientations. The system performance with association to the digit recognition rate has met the design requirement. It has achieved real-time and error-free garment information tracking during the testing.

Improved simultaneous computation of motion detection and optical flow for object tracking

Object tracking systems require accurate segmentation of the objects from the background for effective tracking. Motion segmentation or optical flow can be used to segment incoming images. Whilst optical flow allows multiple moving targets to be separated based on their individual velocities, optical flow techniques are prone to errors caused by changing lighting and occlusions, both common in a surveillance environment. Motion segmentation techniques are more robust to fluctuating lighting and occlusions, but don't provide information on the direction of the motion. In this paper we propose a combined motion segmentation/optical flow algorithm for use in object tracking. The proposed algorithm uses the motion segmentation results to inform the optical flow calculations and ensure that optical flow is only calculated in regions of motion, and improve the performance of the optical flow around the edge of moving objects. Optical flow is calculated at pixel resolution and tracking of flow vectors is employed to improve performance and detect discontinuities, which can indicate the location of overlaps between objects. The algorithm is evaluated by attempting to extract a moving target within the flow images, given expected horizontal and vertical movement (i.e. the algorithms intended use for object tracking). Results show that the proposed algorithm outperforms other widely used optical flow techniques for this surveillance application.