LuxTrace: indoor positioning using building illumination

Tracking location is challenging due to the numerous constraints of practical systems including, but not limited to global cost, device volume and weight, scalability and accuracy; these constraints are typically more severe for systems that should be wearable and used indoors. We investigate the use of wearable solar cells to track changing light conditions (a concept that we named LuxTrace) as a source of user displacement and activity data. We evaluate constraints of this approach and present results from an experimental validation of displacement and activity estimation. The results indicate that a distance estimation accuracy of 21cm (80% quantile) can be achieved. A simple method to combine LuxTrace with complementary absolute location estimation methods is also presented. We apply carpet-like distributed RFID tags to demonstrate online learning of new lighting environment

Forensic Tracking and Surveillance

Digital forensics is an emerging field that has uniquely brought together academics, practitioners and law enforcement. Research in this area was inspired by the numerous challenges posed by the increased sophistication of criminal tools. Traditionally, digital forensics has been confined to the extraction of digital evidence from electronic devices. This direct extraction of digital evidence, however, no longer suffices. Indeed, extracting completely raw data without further processing and/or filtering is, in some cases, useless. These problems can be tackled by the so-called ``computational forensics" where the reconstructs evidence are undertaken further processing. One important application of computational forensics is criminal tracking, which we collectively call ``forensic tracking" and is the main subject of this thesis. This thesis adopts an algorithmic approach to investigate the feasibility of conducting forensic tracking in various environments and settings. Unlike conventional tracking, forensic tracking has to be passive such that the target (who is usually a suspect) should not be aware of the tracking process. We begin by adopting pedestrian setting and propose several online (real-time) forensic tracking algorithms to track a single or multiple targets passively. Beside the core tracking algorithms, we also propose other auxiliary algorithms to improve the robustness and resilience of tracking. We then extend the scope and consider vehicular forensic tracking, where we investigate both online and offline tracking. In online vehicular tracking, we also propose algorithms for motion prediction to estimate the near future movement of target vehicles. Offline vehicular tracking, on the other hand, entails the post-hoc extraction and probabilistic reconstruction of vehicular traces, which we adopt Bayesian approach for. Finally, the contributions of the thesis concludes with building an algorithmic solution for multi-modal tracking, which is a mixed environment combining both pedestrian and vehicular settings

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

The COMPASS Location System

The aim of COMPASS (short for COM mon Positioning Architecture for Several Sensors) is to realize a location infrastructure which can make use of a multitude of different sensors and combine their output in a meaningful way to produce a so called Probability Distribution Function (PDF) that describes the location of a user or device as coordinates and corresponding location probabilities. Furthermore, COMPASS includes a so called translator service, i.e. a build-in component that translates PDFs (or coordinates) to meaningful location identifiers like building names and/or room numbers. This paper gives a short overview on the goals and abilities of COMPASS

Semantic Information Retrieval in the COMPASS Location System

Abstract. In our previous work, we have described the COMPASS location system that uses multiple information sources to determine the current position of a node. The raw output of this process is a location in geo-coordinates, which is not suitable for many applications. In this paper we present an extension to COMPASS, the so called Translator, that can provide facts about the location like city name, address, room number, etc. to the application. These facts are represented in the Semantic Web RDF/XML language and stored on distributed Geo RDF Servers. The main focus of this paper is a location-based service discovery mechanism which allows a node to find all services that can provide facts about its current location. This discovery service is built upon a structured Peer-to-Peer system implementing a distributed hash table.