A Hybrid Indoor Location Positioning System

Indoor location positioning techniques have experienced impressive growth in recent years. A wide range of indoor positioning algorithms has been developed for various applications. In this work a practical indoor location positioning technique is presented which utilizes off-the-shelf smartphones and low-cost Bluetooth Low Energy (BLE) nodes without any further infrastructure. The method includes coarse and fine modes of location positioning. In the coarse mode, the received signal strength (RSS) of the BLE nodes is used for location estimation while in the fine acoustic signals are utilized for accurate positioning. The system can achieve centimeter-level positioning accuracy in its fine mode. To enhance the system’s performance in noisy environments, two digital signal processing (DSP) algorithms of (a) band-pass filtering with audio pattern recognition and (b) linear frequency modulated chirp signal with matched filter are implemented. To increase the system’s robustness in dense multipath environments, a method using data clustering with sliding window is employed. The received signal strength of BLE nodes is used as an auxiliary positioning method to identify the non-line-of-sight (NLoS) propagation paths in the acoustic positioning mode. Experimental measurement results in an indoor area of 10 m2 indicate that the positioning error falls below 6 cm

ATLAS Virtual Visits: Bringing the World into the ATLAS Control Room

The newfound ability of Social Media to transform public communication back to a conversational nature provides HEP with a powerful tool for Outreach and Communication. By far, the most effective component of nearly any visit or public event is that fact that the students, teachers, media, and members of the public have a chance to meet and converse with real scientists. While more than 30,000 visitors passed through the ATLAS Visitor Centre in 2011, nearly 7 billion did not have a chance to make the trip. Clearly this is not for lack of interest. Rather, the costs of travel, in terms of time and money, and limited parking, put that number somewhat out of reach. On the other hand, during the LHC “First Physics” event of 2010, more than 2 million visitors joined the experiment control rooms via webcast for the celebration. This document presents a project developed for the ATLAS Experiment's Outreach and Education program that complements the webcast infrastructure with video conferencing and wireless sound systems, allowing the public to interact with hosts in the control room with minimal disturbance to the shifters. These “Virtual Visits” have included high school classes, LHC Masterclasses, conferences, expositions and other events in Europe, USA, Japan and Australia, to name a few. We discuss the technology used, potential pitfalls (and ways to avoid them), and our plans for the future.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/98637/1/1742-6596_396_6_062008.pd

Device based Multi-User Tracking System using Internet of Things

In Light Dependent Resistor (LDR) sensor-based user is localized based on the event and the intensity of the room light when a user enters inside a room and switch ON the lights, the intensity goes high, an entry is noti?ed. An exit is noti?ed when a user switches OFF the light and exit the room. Moreover, the model remains prone to more error in multi user localization because multiple users may enter inside same room at same time and the lights of many rooms remain ON which makes more difficult to localize a user. In order to overcome this ambiguity of light sensors, two passive infrared (PIR) sensor with radio frequency identi?cation (RFID) tag-based model has been proposed, where every user has a tag. In this system, 10 PIR sensors and 5 RFID readers were attached to house room (10.0 m * 6.0m). An entry is noti?ed if the following pattern form, the outer PIR detects a motion and waits for few seconds, next the RFID reader reads the tag given to the user and ?nally the inner PIR detects a motion within the given time delay. An exit of a user is noti?ed only if the pattern from inner PIR to outer PIR is followed with the given time delay. The RFID tag is used to identify which user has entered a room at a particular time and also ensures unauthorized entry. The LDR based system gives accuracy nearby 20% but the multi-person tracking in a binary infrared sensor network-based system gives accuracy near about 90%. In this paper, the proposed PIR sensor along with RFID based indoor navigation system gives accuracy near about 94%.                              &nbsp

GNSS-free outdoor localization techniques for resource-constrained IoT architectures : a literature review

Large-scale deployments of the Internet of Things (IoT) are adopted for performance improvement and cost reduction in several application domains. The four main IoT application domains covered throughout this article are smart cities, smart transportation, smart healthcare, and smart manufacturing. To increase IoT applicability, data generated by the IoT devices need to be time-stamped and spatially contextualized. LPWANs have become an attractive solution for outdoor localization and received significant attention from the research community due to low-power, low-cost, and long-range communication. In addition, its signals can be used for communication and localization simultaneously. There are different proposed localization methods to obtain the IoT relative location. Each category of these proposed methods has pros and cons that make them useful for specific IoT systems. Nevertheless, there are some limitations in proposed localization methods that need to be eliminated to meet the IoT ecosystem needs completely. This has motivated this work and provided the following contributions: (1) definition of the main requirements and limitations of outdoor localization techniques for the IoT ecosystem, (2) description of the most relevant GNSS-free outdoor localization methods with a focus on LPWAN technologies, (3) survey the most relevant methods used within the IoT ecosystem for improving GNSS-free localization accuracy, and (4) discussion covering the open challenges and future directions within the field. Some of the important open issues that have different requirements in different IoT systems include energy consumption, security and privacy, accuracy, and scalability. This paper provides an overview of research works that have been published between 2018 to July 2021 and made available through the Google Scholar database.5311-8814-F0ED | Sara Maria da Cruz Maia de Oliveira PaivaN/

Counting chirps : acoustic monitoring of cryptic frogs

Funding for the frog survey was received from the National Geographic Society/Waitt Grants Program (No. W184-11). The EPSRC and NERC helped to fund this research through a PhD grant (No. EP/1000917/1) to D.L.B. R.A. and G.J.M. acknowledge initiative funding from the National Research Foundation of South Africa.1 .  Global amphibian declines have resulted in a vital need for monitoring programmes that follow population trends. Monitoring using advertisement calls is ideal as choruses are undisturbed during data collection. However, methods currently employed by managers frequently rely on trained observers, and/or do not provide density data on which to base trends. 2 .  This study explores the utility of monitoring using acoustic spatially explicit capture-recapture (aSECR) with time of arrival (ToA) and signal strength (SS) as a quantitative monitoring technique to measure call density of a threatened but visually cryptic anuran, the Cape peninsula moss frog Arthroleptella lightfooti. 3 .  The relationships between temporal and environmental variables (date, rainfall, temperature) and A. lightfooti call density at three study sites on the Cape peninsula, South Africa were examined. Acoustic data, collected from an array of six microphones over four months during the winter breeding season, provided a time series of call density estimates. 4 .  Model selection indicated that call density was primarily associated with seasonality fitted as a quadratic function. Call density peaked mid-breeding season. At the main study site, the lowest recorded mean call density (0·160 calls m-2 min-1) occurred in May and reached its peak mid-July (1·259 calls m-2 min-1). The sites differed in call density, but also the effective sampling area. 5 .  Synthesis and applications.The monitoring technique, acoustic spatially explicit capture–recapture (aSCR), quantitatively estimates call density without disturbing the calling animals or their environment, while time of arrival (ToA) and signal strength (SS) significantly add to the accuracy of call localisation, which in turn increases precision of call density estimates without the need for specialist field staff. This technique appears ideally suited to aid the monitoring of visually cryptic, acoustically active species.Publisher PDFPeer reviewe

A radiosity-based method to avoid calibration for Indoor Positioning Systems

Due to the widespread use of mobile devices, services based on the users current indoor location are growing in significance. Such services are developed in the Machine Learning and Experst Systems realm, and ranges from guidance for blind people to mobile tourism and indoor shopping. One of the most used techniques for indoor positioning is WiFi fingerprinting, being its use of widespread WiFi signals one of the main reasons for its popularity, mostly on high populated urban areas. Most issues of this approach rely on the data acquisition phase; to manually sample WiFi RSSI signals in order to create a WiFi radio map is a high time consuming task, also subject to re-calibrations, because any change in the environment might affect the signal propagation, and therefore degrade the performance of the positioning system. The work presented in this paper aims at substituting the manual data acquisition phase by directly calculating the WiFi radio map by means of a radiosity signal propagation model. The time needed to acquire the WiFi radio map by means of the radiosity model dramatically reduces from hours to minutes when compared with manual acquisition. The proposed method is able to produce competitive results, in terms of accuracy, when compared with manual sampling, which can help domain experts develop services based on location faster

Indoor outdoor detection

Abstract. This thesis shows a viable machine learning model that detects Indoor or Outdoor on smartphones. The model was designed as a classification problem and it was trained with data collected from several smartphone sensors by participants of a field trial conducted. The data collected was labeled manually either indoor or outdoor by the participants themselves. The model was then iterated over to lower the energy consumption by utilizing feature selection techniques and subsampling techniques. The model which uses all of the data achieved a 99 % prediction accuracy, while the energy efficient model achieved 92.91 %. This work provides the tools for researchers to quantify environmental exposure using smartphones

TOA Estimation of Chirp Signal in Dense Multipath Environment for Low-Cost Acoustic Ranging

In this paper, a novel time of arrival (TOA) estimation method is proposed based on an iterative cleaning process to extract the first path signal. The purpose is to address the challenge in dense multipath indoor environments that the power of the first path component is normally smaller than other multipath components, where the traditional match filtering (MF)-based TOA estimator causes huge errors. Along with parameter estimation, the proposed process is trying to detect and extract the first path component by eliminating the strongest multipath component using a band-elimination filter in fractional Fourier domain at each iterative procedure. To further improve the stability, a slack threshold and a strict threshold are introduced. Six simple and easily calculated termination criteria are proposed to monitor the iterative process. When the iterative 'cleaning' process is done, the outputs include the enhanced first path component and its estimated parameters. Based on these outputs, an optimal reference signal for the MF estimator can be constructed, and a more accurate TOA estimation can be conveniently obtained. The results from numerical simulations and experimental investigations verified that, for acoustic chirp signal TOA estimation, the accuracy of the proposed method is superior to those obtained by the conventional MF estimators

Desenvolvimento de metodologias para localização indoor de smartphones com exatidão ao centímetro

Doutoramento em Engenharia ElectrotécnicaThis thesis describes the design and implementation of a reliable centimeter-level indoor positioning system fully compatible with a conventional smartphone. The proposed system takes advantage of the smartphone audio I/O and processing capabilities to perform acoustic ranging in the audio band using non-invasive audio signals and it has been developed having in mind applications that require high accuracy, such as augmented reality, virtual reality, gaming and audio guides. The system works in a distributed operation mode, i.e. each smartphone is able to obtain its own position using only acoustic signals. To support the positioning system, a Wireless Sensor Network (WSN) of synchronized acoustic beacons is used. To keep the infrastructure in sync we have developed an Automatic Time Synchronization and Syntonization (ATSS) protocol with a standard deviation of the sync offset error below 1.25 μs. Using an improved Time Difference of Arrival (TDoA) estimation approach (which takes advantage of the beacon signals’ periodicity) and by performing Non-Line-of-Sight (NLoS) mitigation, we were able to obtain very stable and accurate position estimates with an absolute mean error of less than 10 cm in 95% of the cases and a mean standard deviation of 2.2 cm for a position refresh period of 350 ms.Esta tese descreve o projeto e a implementação de um sistema de localização para ambientes interiores totalmente compatível com um smartphone convencional. O sistema proposto explora a capacidade de aquisição de sinais áudio e de processamento do smartphone para medir distâncias utilizando sinais acústicos na banda do audível; foram utilizados sinais áudio não-invasivos, i.e. com reduzido impacto perceptual em humanos. No desenvolvimento deste sistema foram consideradas aplicações que exigem elevada exatidão, na ordem dos centímetros, tais como realidade aumentada, realidade virtual, jogos ou guias virtuais. Utilizou-se uma infraestrutura de faróis de baixo custo suportada por uma rede de sensores sem fios (RSSF). Para manter a infraestrutura síncrona, foi desenvolvido um protocolo de sincronização e sintonização automática, (Automatic Time Synchronization and Syntonization - ATSS) que garante um desvio padrão do erro de offset abaixo de 1.25 μs. Cada smartphone efectua medidas MT-TDoA que posteriormente são utilizadas pelo algoritmo de localização hiperbólica. As estimativas de posição resultantes são estáveis e precisas, com um erro médio absoluto menor do que 10 cm em 95% dos casos e um desvio padrão médio de 2.2 cm, para um período de atualização de posição de 350 ms

Audio beacon technologies, surveillance and social order

This thesis explores audio beacon technology with the aim of elucidating the implications of this technology for the individual in contemporary society. Audio beacons are hidden inside digital devices. They emit and receive high frequency audio signals which are inaudible to the human ear, thereby generating and transmitting data without our knowledge. The motivation for this research is to raise awareness of the prevalence of audio beacon technologies and to explore their implications for contemporary society. The research takes an interdisciplinary approach involving – 1) a survey of audio beacon technology, 2) a contextualization in terms of contemporary theories of surveillance and control and 3) an interpretation in terms of 20th century dystopian literature. The hidden surveillance and privacy of this technology is examined mainly through the humanistic perspective of George Orwell’s book Nineteen Eighty-Four. The general conclusion formed is that audio beacon technologies can serve as a surveillance method enhancing authoritarian and exploitative regimes. To mitigate the negative impacts of audio beacons, this research proposes two types of solutions – 1) individual actions that will have an immediate effect and 2) governmental legislation that can improve privacy in the longer term. Both of these solutions cannot happen without a raised public awareness, towards which this research hopes to make a contribution. Finally, this research introduces the notion of a \u27digital paradox\u27 in which the dystopian worlds of George Orwell and Aldous Huxley are brought together in order to characterize surveillance and control in contemporary society