2 research outputs found
Sistemas de posicionamento baseados em comunicação por luz para ambientes interiores
The demand for highly precise indoor positioning systems (IPSs) is growing
rapidly due to its potential in the increasingly popular techniques of the
Internet of Things, smart mobile devices, and artificial intelligence. IPS
becomes a promising research domain that is getting wide attention due to its
benefits in several working scenarios, such as, industries, indoor public
locations, and autonomous navigation. Moreover, IPS has a prominent
contribution in day-to-day activities in organizations such as health care
centers, airports, shopping malls, manufacturing, underground locations, etc.,
for safe operating environments. In indoor environments, both radio frequency
(RF) and optical wireless communication (OWC) based technologies could be
adopted for localization. Although the RF-based global positioning system,
such as, Global positioning system offers higher penetration rates with
reduced accuracy (i.e., in the range of a few meters), it does not work well in
indoor environments (and not at all in certain cases such as tunnels, mines,
etc.) due to the very weak signal and no direct access to the satellites. On the
other hand, the light-based system known as a visible light positioning (VLP)
system, as part of the OWC systems, uses the pre-existing light-emitting
diodes (LEDs)-based lighting infrastructure, could be used at low cost and
high accuracy compared with the RF-based systems. VLP is an emerging
technology promising high accuracy, high security, low deployment cost,
shorter time response, and low relative complexity when compared with RFbased
positioning.
However, in indoor VLP systems, there are some concerns such as,
multipath reflection, transmitter tilting, transmitter’s position, and orientation
uncertainty, human shadowing/blocking, and noise causing the increase in
the positioning error, thereby reducing the positioning accuracy of the system.
Therefore, it is imperative to capture the characteristics of different VLP
channel and properly model them for the dual purpose of illumination and
localization. In this thesis, firstly, the impact of transmitter tilting angles and
multipath reflections are studied and for the first time, it is demonstrated that
tilting the transmitter can be beneficial in VLP systems considering both line of
sight (LOS) and non-line of sight transmission paths. With the transmitters
oriented towards the center of the receiving plane, the received power level is
maximized due to the LOS components. It is also shown that the proposed
scheme offers a significant accuracy improvement of up to ~66% compared
with a typical non-tilted transmitter VLP. The effect of tilting the transmitter on
the lighting uniformity is also investigated and results proved that the
uniformity achieved complies with the European Standard EN 12464-1.
After that, the impact of transmitter position and orientation uncertainty on
the accuracy of the VLP system based on the received signal strength (RSS)
is investigated. Simulation results show that the transmitter uncertainties have
a severe impact on the positioning error, which can be leveraged through the
usage of more transmitters. Concerning a smaller transmitter’s position
epochs, and the size of the training set. It is shown that,
the ANN with Bayesian regularization outperforms the traditional RSS
technique using the non-linear least square estimation for all values of signal
to noise ratio.
Furthermore, a novel indoor VLP system is proposed based on support
vector machines and polynomial regression considering two different
multipath environments of an empty room and a furnished room. The results
show that, in an empty room, the positioning accuracy improvement for the
positioning error of 2.5 cm are 36.1, 58.3, and 72.2 % for three different
scenarios according to the regions’ distribution in the room. For the furnished
room, a positioning relative accuracy improvement of 214, 170, and 100 % is
observed for positioning error of 0.1, 0.2, and 0.3 m, respectively. Ultimately,
an indoor VLP system based on convolutional neural networks (CNN) is
proposed and demonstrated experimentally in which LEDs are used as
transmitters and a rolling shutter camera is used as receiver. A detection
algorithm named single shot detector (SSD) is used which relies on CNN (i.e.,
MobileNet or ResNet) for classification as well as position estimation of each
LED in the image. The system is validated using a real-world size test setup
containing eight LED luminaries. The obtained results show that the maximum
average root mean square positioning error achieved is 4.67 and 5.27 cm with
SSD MobileNet and SSD ResNet models, respectively. The validation results
show that the system can process 67 images per second, allowing real-time
positioning.A procura por sistemas de posicionamento interior (IPSs) de alta precisão tem
crescido rapidamente devido ao seu interesse nas técnicas cada vez mais
populares da Internet das Coisas, dispositivos móveis inteligentes e
inteligência artificial. O IPS tornou-se um domínio de pesquisa promissor que
tem atraído grande atenção devido aos seus benefícios em vários cenários de
trabalho, como indústrias, locais públicos e navegação autónoma. Além disso,
o IPS tem uma contribuição destacada no dia a dia de organizações, como,
centros de saúde, aeroportos, supermercados, fábricas, locais subterrâneos,
etc. As tecnologias baseadas em radiofrequência (RF) e comunicação óptica
sem fio (OWC) podem ser adotadas para localização em ambientes interiores.
Embora o sistema de posicionamento global (GPS) baseado em RF ofereça
taxas de penetração mais altas com precisão reduzida (ou seja, na faixa de
alguns metros), não funciona bem em ambientes interiores (e não funciona
bem em certos casos como túneis, minas, etc.) devido ao sinal muito fraco e
falta de acesso direto aos satélites. Por outro lado, o sistema baseado em luz
conhecido como sistema de posicionamento de luz visível (VLP), como parte
dos sistemas OWC, usa a infraestrutura de iluminação baseada em díodos
emissores de luz (LEDs) pré-existentes, é um sistemas de baixo custo e alta
precisão quando comprado com os sistemas baseados em RF. O VLP é uma
tecnologia emergente que promete alta precisão, alta segurança, baixo custo
de implantação, menor tempo de resposta e baixa complexidade relativa
quando comparado ao posicionamento baseado em RF.
No entanto, os sistemas VLP interiores, exibem algumas limitações, como, a
reflexão multicaminho, inclinação do transmissor, posição do transmissor e
incerteza de orientação, sombra/bloqueio humano e ruído, que têm como
consequência o aumento do erro de posicionamento, e consequente redução
da precisão do sistema. Portanto, é imperativo estudar as características dos
diferentes canais VLP e modelá-los adequadamente para o duplo propósito de
iluminação e localização. Esta tesa aborda, primeiramente, o impacto dos
ângulos de inclinação do transmissor e reflexões multipercurso no
desempenho do sistema de posicionamento. Demonstra-se que a inclinação
do transmissor pode ser benéfica em sistemas VLP considerando tanto a linha
de vista (LOS) como as reflexões. Com os transmissores orientados para o
centro do plano recetor, o nível de potência recebido é maximizado devido aos
componentes LOS. Também é mostrado que o esquema proposto oferece
uma melhoria significativa de precisão de até ~66% em comparação com um
sistema VLP de transmissor não inclinado típico. O efeito da inclinação do
transmissor na uniformidade da iluminação também é investigado e os
resultados comprovam que a uniformidade alcançada está de acordo com a
Norma Europeia EN 12464-1.
O impacto da posição do transmissor e incerteza de orientação na precisão
do sistema VLP com base na intensidade do sinal recebido (RSS) foi também investigado. Os resultados da simulação mostram que as incertezas do
transmissor têm um impacto severo no erro de posicionamento, que pode ser
atenuado com o uso de mais transmissores. Para incertezas de
posicionamento dos transmissores menores que 5 cm, os erros médios de
posicionamento são 23.3, 15.1 e 13.2 cm para conjuntos de 4, 9 e 16
transmissores, respetivamente. Enquanto que, para a incerteza de orientação
de um transmissor menor de 5°, os erros médios de posicionamento são 31.9,
20.6 e 17 cm para conjuntos de 4, 9 e 16 transmissores, respetivamente.
O trabalho da tese abordou a investigação dos aspetos de projeto de um
sistema VLP indoor no qual uma rede neuronal artificial (ANN) é utilizada para
estimativa de posicionamento considerando um canal multipercurso. O estudo
considerou a influência do ruído como indicador de desempenho para a
comparação entre diferentes abordagens de projeto. Três algoritmos de treino
de ANNs diferentes foram considerados, a saber, Levenberg-Marquardt,
regularização Bayesiana e algoritmos de gradiente conjugado escalonado,
para minimizar o erro de posicionamento no sistema VLP. O projeto da ANN foi
otimizado com base no número de neurónios nas camadas ocultas, no número
de épocas de treino e no tamanho do conjunto de treino. Mostrou-se que, a
ANN com regularização Bayesiana superou a técnica RSS tradicional usando
a estimação não linear dos mínimos quadrados para todos os valores da
relação sinal-ruído.
Foi proposto um novo sistema VLP indoor baseado em máquinas de vetores
de suporte (SVM) e regressão polinomial considerando dois ambientes
interiores diferentes: uma sala vazia e uma sala mobiliada. Os resultados
mostraram que, numa sala vazia, a melhoria da precisão de posicionamento
para o erro de posicionamento de 2.5 cm são 36.1, 58.3 e 72.2% para três
cenários diferentes de acordo com a distribuição das regiões na sala. Para a
sala mobiliada, uma melhoria de precisão relativa de posicionamento de 214,
170 e 100% é observada para erro de posicionamento de 0.1, 0.2 e 0.3 m,
respetivamente.
Finalmente, foi proposto um sistema VLP indoor baseado em redes neurais
convolucionais (CNN). O sistema foi demonstrado experimentalmente usando
luminárias LED como transmissores e uma camara com obturador rotativo
como recetor. O algoritmo de detecção usou um detector de disparo único
(SSD) baseado numa CNN pré configurada (ou seja, MobileNet ou ResNet)
para classificação. O sistema foi validado usando uma configuração de teste
de tamanho real contendo oito luminárias LED. Os resultados obtidos
mostraram que o erro de posicionamento quadrático médio alcançado é de
4.67 e 5.27 cm com os modelos SSD MobileNet e SSD ResNet,
respetivamente. Os resultados da validação mostram que o sistema pode
processar 67 imagens por segundo, permitindo o posicionamento em tempo
real.Programa Doutoral em Engenharia Eletrotécnic
Visible Light and Camera-based Receiver Employing Machine Learning for Indoor Positioning Systems and Data Communications
Indoor location-based services have played a crucial role in the development of various Internet of Things applications over the last few decades. The use of radio frequency (RF)-based systems in indoor environments suffers from additional interference due to the high penetration rate and reflections of the RF, which may severely affect positioning accuracy. Alternatively, the optical technology using the existing light-emitting diode (LED)-based lights, photodetectors (PDs), and/or image sensors could be utilised to provide indoor positioning with high accuracy. Because of its resilience to electromagnetic interference, license-free operation, large bandwidth, and dual-use for illumination and communication, visible light positioning (VLP) systems have shown great potential in achieving high-precision indoor positioning. This thesis focus is on investigating VLP systems based on employing a single PD, or an array of PDs in the form of a single image sensor (i.e. a camera) for both localization and data communication. Following a comprehensive literature review on VLP, the key challenges in existing positioning methods for achieving a low-cost, accurate, and less complex indoor positioning systems design are highlighted by considering the design characteristics of an indoor environment, position accuracy, number of light-emitting LED, PD, and any additional sensors utilized. The thesis focuses on the major constraints of VLP and provides novel contributions. In most reported VLP schemes, the assumptions of fixed transmitter (Tx) angle and height may not be valid in many physical environments. In this work, the impact of tilting Tx and multipath reflections are investigated. The findings demonstrated that tilting Tx can be beneficial in VLP by leveraging the influence of reflections from both near- and far-walls. It also showed that proposed system offers a significant accuracy improvement by up to ~66% compared with a typical non-tilted Tx VLP system.Furthermore, increasing robustness of image sensor-based receiver (Rx) is a major challenge, which is being addressed using a novel angle of arrival-received signal intensity and a single LED. Experimental results show that the proposed algorithm can achieve a three-dimensional root mean squared error of 7.56 cm. Visible light communications employing a camera-based Rx is best known as optical camera communications (OCC), which can also be used for VLP. However, in OCC the transmission data rate is mainly limited by the exposure time and the frame rate of the camera. In addition, the camera's sampling introduces intersymbol interference Indoor location-based services have played a crucial role in the development of various Internet of Things applications over the last few decades. The use of radio frequency (RF)-based systems in indoor environments suffers from additional interference due to the high penetration rate and reflections of the RF, which may severely affect positioning accuracy. Alternatively, the optical technology using the existing light-emitting diode (LED)-based lights, photodetectors (PDs), and/or image sensors could be utilised to provide indoor positioning with high accuracy. Because of its resilience to electromagnetic interference, license-free operation, large bandwidth, and dual-use for illumination and communication, visible light positioning (VLP) systems have shown great potential in achieving high-precision indoor positioning. This thesis focus is on investigating VLP systems based on employing a single PD, or an array of PDs in the form of a single image sensor (i.e. a camera) for both localization and data communication. Following a comprehensive literature review on VLP, the key challenges in existing positioning methods for achieving a low-cost, accurate, and less complex indoor positioning systems design are highlighted by considering the design characteristics of an indoor environment, position accuracy, number of light-emitting LED, PD, and any additional sensors utilized. The thesis focuses on the major constraints of VLP and provides novel contributions. In most reported VLP schemes, the assumptions of fixed transmitter (Tx) angle and height may not be valid in many physical environments. In this work, the impact of tilting Tx and multipath reflections are investigated. The findings demonstrated that tilting Tx can be beneficial in VLP by leveraging the influence of reflections from both near- and far-walls. It also showed that proposed system offers a significant accuracy improvement by up to ~66% compared with a typical non-tilted Tx VLP system.Furthermore, increasing robustness of image sensor-based receiver (Rx) is a major challenge, which is being addressed using a novel angle of arrival-received signal intensity and a single LED. Experimental results show that the proposed algorithm can achieve a three-dimensional root mean squared error of 7.56 cm. Visible light communications employing a camera-based Rx is best known as optical camera communications (OCC), which can also be used for VLP. However, in OCC the transmission data rate is mainly limited by the exposure time and the frame rate of the camera. In addition, the camera's sampling introduces intersymbol interference