Vehicular Visible Light Positioning System Based on a PSD Detector.

In this paper, we explore the use of visible light positioning (VLP) technology in vehicles in intelligent transportation systems (ITS), highlighting its potential for maintaining effective line of sight (LOS) and providing high-accuracy positioning between vehicles. The proposed system (V2V-VLP) is based on a position-sensitive detector (PSD) and exploiting car taillights to determine the position and inter-vehicular distance by angle of arrival (AoA) measurements. The integration of the PSD sensor in vehicles promises exceptional positioning accuracy, opening new prospects for navigation and driving safety. The results revealed that the proposed system enables precise measurement of position and distance between vehicles, including lateral distance. We evaluated the impact of different focal lengths on the system performance, achieving cm-level accuracy for distances up to 35 m, with an optimum focal length of 25 mm, and under low signal-to-noise conditions, which meets the standards required for safe and reliable V2V applications. Several experimental tests were carried out to validate the results of the simulations.

Accuracy and Precision of Agents Orientation in an Indoor Positioning System Using Multiple Infrastructure Lighting Spotlights and a PSD Sensor.

In indoor localization there are applications in which the orientation of the agent to be located is as important as knowing the position. In this paper we present the results of the orientation estimation from a local positioning system based on position-sensitive device (PSD) sensors and the visible light emitted from the illumination of the room in which it is located. The orientation estimation will require that the PSD sensor receives signal from either 2 or 4 light sources simultaneously. As will be shown in the article, the error determining the rotation angle of the agent with the on-board sensor is less than 0.2 degrees for two emitters. On the other hand, by using 4 light sources the three Euler rotation angles are determined, with mean errors in the measurements smaller than 0.35° for the x- and y-axis and 0.16° for the z-axis. The accuracy of the measurement has been evaluated experimentally in a 2.5 m-high ceiling room over an area of 2.2 m2 using geodetic measurement tools to establish the reference ground truth values.

Dynamic Insulin Basal Needs Estimation and Parameters Adjustment in Type 1 Diabetes.

Technology advances have made possible improvements such as Continuous Glucose Monitors, giving the patient a glucose reading every few minutes, or insulin pumps, allowing more personalized therapies. With the increasing number of available closed-loop systems, new challenges appear regarding algorithms and functionalities. Several of the analysed systems in this paper try to adapt to changes in some patients' conditions and, in several of these systems, other variables such as basal needs are considered fixed from day to day to simplify the control problem. Therefore, these systems require a correct adjustment of the basal needs profile which becomes crucial to obtain good results. In this paper a novel approach tries to dynamically determine the insulin basal needs of the patient and use this information within a closed-loop algorithm, allowing the system to dynamically adjust in situations of illness, exercise, high-fat-content meals or even partially blocked infusion sites and avoiding the need for setting a basal profile that approximately matches the basal needs of the patient. The insulin sensitivity factor and the glycemic target are also dynamically modified according to the situation of the patient. Basal insulin needs are dynamically determined through linear regression via the decomposition of previously dosed insulin and its effect on the patient's glycemia. Using the obtained value as basal insulin needs and other mechanisms such as basal needs modification through its trend, ISF and glycemic targets modification and low-glucose-suspend threshold, the safety of the algorithm is improved. The dynamic basal insulin needs determination was successfully included in a closed-loop control algorithm and was simulated on 30 virtual patients (10 adults, 10 adolescent and 10 children) using an open-source python implementation of the FDA-approved (Food and Drug Administration) UVa (University of Virginia)/Padova Simulator. Simulations showed that the proposed system dynamically determines the basal needs and can adapt to a partial blockage of the insulin infusion, obtaining similar results in terms of time in range to the case in which no blockage was simulated. The proposed algorithm can be incorporated to other current closed-loop control algorithms to directly estimate the patient's basal insulin needs or as a monitoring channel to detect situations in which basal needs may differ from the expected ones.

Weak Calibration of a Visible Light Positioning System Based on a Position-Sensitive Detector: Positioning Error Assessment.

Reduced deployment and calibration requirements are key for scalable and cost-effective indoor positioning systems. In this work, we propose a low-complexity, weak calibration procedure for an indoor positioning system based on infrastructure lighting and a positioning-sensitive detector. The proposed calibration relies on genetic algorithms to obtain the relevant system parameters in the real positioning environment without a priori information, and requires a low number of simple measurements. The achievable performance of the proposal was assessed by direct comparison with a formal offline calibration method requiring complex dedicated infrastructure and instruments. The comparative error assessment showed that the maximum accuracy reduction compared to the significantly more costly formal calibration was below 25 mm, and the overall absolute positioning error was smaller than 35 mm with orientation errors of around 0.25°. The performance achieved with the proposed weak calibration procedure is sufficient for many indoor positioning applications and largely reduces the cost and complexity of setting up the positioning system in real environments.

Smart Video Surveillance System Based on Edge Computing.

New processing methods based on artificial intelligence (AI) and deep learning are replacing traditional computer vision algorithms. The more advanced systems can process huge amounts of data in large computing facilities. In contrast, this paper presents a smart video surveillance system executing AI algorithms in low power consumption embedded devices. The computer vision algorithm, typical for surveillance applications, aims to detect, count and track people's movements in the area. This application requires a distributed smart camera system. The proposed AI application allows detecting people in the surveillance area using a MobileNet-SSD architecture. In addition, using a robust Kalman filter bank, the algorithm can keep track of people in the video also providing people counting information. The detection results are excellent considering the constraints imposed on the process. The selected architecture for the edge node is based on a UpSquared2 device that includes a vision processor unit (VPU) capable of accelerating the AI CNN inference. The results section provides information about the image processing time when multiple video cameras are connected to the same edge node, people detection precision and recall curves, and the energy consumption of the system. The discussion of results shows the usefulness of deploying this smart camera node throughout a distributed surveillance system.

Accuracy and Precision Assessment of AoA-Based Indoor Positioning Systems Using Infrastructure Lighting and a Position-Sensitive Detector.

Unlike GNSS-based outdoor positioning, there is no technological alternative for Indoor Positioning Systems (IPSs) that generally stands out from the others. In indoor contexts, the measurement technologies and localization strategies to be used depend strongly on the application requirements and are complementary to each other. In this work, we present an optical IPS based on a Position-Sensitive Detector (PSD) and exploiting illumination infrastructure to determine the target position by Angle of Arrival (AoA) measurements. We combine the proposed IPS with different positioning strategies depending on the number of visible emitters (one, two, or more) and available prior or additional information about the scenario and target. The accuracy and precision of the proposal is assessed experimentally for the different strategies in a 2.47 m high space covering approximately 2.2 m2, using high-end geodetic equipment to establish the reference ground truth. When the orientation of the target is known from external measurements, an average positioning error of 8.2 mm is obtained using the signal received from only one emitter. Using simultaneous observations from two emitters, an average positioning error of 9.4 mm is obtained without external information when the target movement is restricted to a plane. Conversely, if four signals are available, an average positioning error of 4.9 cm is demonstrated, yielding the complete 3D pose of the target free of any prior assumption or additional measurements. In all cases, a precision (2σ) better than 5.9 mm is achieved across the complete test space for an integration time of 10 ms. The proposed system represents a prospectively useful alternative for indoor positioning applications requiring fast and reliable cm-level accuracy with moderate cost when smart illumination infrastructure is available in the environment.

Analysis of Multiple-Access Discrimination Techniques for the Development of a PSD-Based VLP System.

There are several technologies and techniques available when developing indoor positioning systems (IPS). Recently, the development of positioning systems based on optical signals has aroused great interest, mainly those using visible light from the lighting infrastructure. In this work, we analyze which techniques give better results to lay the foundations for the development of a Visible Light Positioning system (VLP). Working only with a receiver, it is analyzed what the result of determining the position of different emitters is when they emit simultaneously and without any synchronism. The results obtained by Frequency Division Multiple Access (FDMA) (with digital bandpass filters, I/Q demodulation, and FFT) and Code Division Multiple Access (CDMA) are compared. The interference between signals when emitted simultaneously from multiple emitters is analyzed as well as the errors they cause and how these effects can be mitigated. As a result of the research, the advantages and disadvantages using different multiple-access determination techniques are determined. In addition, advantages and disadvantages of using FDMA and CDMA techniques as well as hardware requirements that make one more feasible than the other are presented. The system behavior, in terms of errors, is established using FDMA and different configurations such as: I/Q, RMS, or FFT. The work also determines the error rates that can be obtained with the different FDMA and CDMA configurations, considering different error scenarios and integration time. Synthetic emulations and empirical tests were performed, which concluded that IPS systems based on optical signals and PSD sensors can achieve very high measurement accuracies and a high measurement rate. Obtained positioning errors in a room of 3 m height are less than 1 cm when working in noisy environments.

Characterization of Multipath Effects in Indoor Positioning Systems by AoA and PoA Based on Optical Signals.

In this paper, we characterize and measure the effects of the errors introduced by the multipath when obtaining the position of an agent by means of Indoor Positioning Systems (IPS) based on optical signal. These effects are characterized in Local Positioning Systems (LPSs) based on two different techniques: the first one by determining the Angle of Arrival (AoA) of the infrared signal (IR) to the detector; and the second one by working with the measurement of the Phase shift of signal Arrival from the transmitter to a receiver (PoA). We present the obtained results and conclusions, which indicate that using Position Sensitive Devices (PSD) the multipath effects for AoA have little impact on the measurement, while for PoA the positioning errors are very significant, making the system useless in many cases.

Modeling the Effect of Optical Signal Multipath.

Here, we propose a model to determine the effect of multipath in indoor environments when the shape and characteristics of the environment are known. The main paper goal is to model the multipath signal formation to solve, as much as possible, the negative effects in light communications, as well as the indoor positioning errors due to this phenomenon when using optical signals. The methodology followed was: analyze the multipath phenomenon, establish a theoretical approach and propose different models to characterize the behavior of the channel, emitter and receiver. The channel impulse response and received signal strength are obtained from different proposed algorithms. We also propose steps for implementing a numerical procedure to calculate the effects of these multipaths using information that characterizes the environment, transmitter and receiver and their corresponding positions. In addition, the results of an empirical test in a controlled environment are compared with those obtained using the model, in order to validate the latter. The results may largely vary with respect to the cell size used to discretize the environment. We have concluded that a cell size whose side is 20-times smaller than the minimum distance between emitter and receiver (i.e., 10 cm × 10 cm for a 2-m distance) provides almost identical results between the empirical tests and the proposed model, with an affordable computational load.

Indoor Positioning System Based on a PSD Detector, Precise Positioning of Agents in Motion Using AoA Techniques.

Here, we present an indoor positioning system (IPS) for detecting mobile agents based on a single Position Sensitive Device sensor (PSD) sited in the environment and InfraRed Emitter Diode (IRED) located on mobile agents. The main goal of the work is to develop an alternative IPS to other sensing technologies, cheaper, easier to install and with a low computational load to obtain a high rate of measurements per second. The proposed IPS has the capacity to accurately determine 3D position from the angle of arrival (AoA) of the signal received at the PSD sensor. In this first approach to the method, the agents are considered to move along a plane. We propose two alternatives for determining position: in one, tones are emitted on a frequency unique to each transmitter, while in the other, sequences are emitted.The paper proposes and set up a very simple and easy to deploy system capable of performing 3D positioning with a single analog sensor, obtaining a high accurate positioning and a reduced execution time for the signal processing. The low computational load of the IPS makes it possible to obtain a very high position update rate (more than 100 times per second), yielding millimetric accuracies.

Modeling Infrared Signal Reflections to Characterize Indoor Multipath Propagation.

In this paper, we propose a model to characterize Infrared (IR) signal reflections on any kind of surface material, together with a simplified procedure to compute the model parameters. The model works within the framework of Local Positioning Systems (LPS) based on IR signals (IR-LPS) to evaluate the behavior of transmitted signal Multipaths (MP), which are the main cause of error in IR-LPS, and makes several contributions to mitigation methods. Current methods are based on physics, optics, geometry and empirical methods, but these do not meet our requirements because of the need to apply several different restrictions and employ complex tools. We propose a simplified model based on only two reflection components, together with a method for determining the model parameters based on 12 empirical measurements that are easily performed in the real environment where the IR-LPS is being applied. Our experimental results show that the model provides a comprehensive solution to the real behavior of IR MP, yielding small errors when comparing real and modeled data (the mean error ranges from 1% to 4% depending on the environment surface materials). Other state-of-the-art methods yielded mean errors ranging from 15% to 40% in test measurements.

Erratum: Rodríguez-Navarro, D., et al. Mathematical Model and Calibration Procedure of a PSD Sensor Used in Local Positioning Systems. Sensors 2016, 16, 1484.

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Mathematical Model and Calibration Procedure of a PSD Sensor Used in Local Positioning Systems.

Here, we propose a mathematical model and a calibration procedure for a PSD (position sensitive device) sensor equipped with an optical system, to enable accurate measurement of the angle of arrival of one or more beams of light emitted by infrared (IR) transmitters located at distances of between 4 and 6 m. To achieve this objective, it was necessary to characterize the intrinsic parameters that model the system and obtain their values. This first approach was based on a pin-hole model, to which system nonlinearities were added, and this was used to model the points obtained with the nA currents provided by the PSD. In addition, we analyzed the main sources of error, including PSD sensor signal noise, gain factor imbalances and PSD sensor distortion. The results indicated that the proposed model and method provided satisfactory calibration and yielded precise parameter values, enabling accurate measurement of the angle of arrival with a low degree of error, as evidenced by the experimental results.

Analysis and Calibration of Sources of Electronic Error in PSD Sensor Response.

In order to obtain very precise measurements of the position of agents located at a considerable distance using a sensor system based on position sensitive detectors (PSD), it is necessary to analyze and mitigate the factors that generate substantial errors in the system's response. These sources of error can be divided into electronic and geometric factors. The former stem from the nature and construction of the PSD as well as the performance, tolerances and electronic response of the system, while the latter are related to the sensor's optical system. Here, we focus solely on the electrical effects, since the study, analysis and correction of these are a prerequisite for subsequently addressing geometric errors. A simple calibration method is proposed, which considers PSD response, component tolerances, temperature variations, signal frequency used, signal to noise ratio (SNR), suboptimal operational amplifier parameters, and analog to digital converter (ADC) quantitation SNRQ, etc. Following an analysis of these effects and calibration of the sensor, it was possible to correct the errors, thus rendering the effects negligible, as reported in the results section.

Improving the calibration of image sensors based on IOFBs, using differential gray-code space encoding.

This paper presents a fast calibration method to determine the transfer function for spatial correspondences in image transmission devices with Incoherent Optical Fiber Bundles (IOFBs), by performing a scan of the input, using differential patterns generated from a Gray code (Differential Gray-Code Space Encoding, DGSE). The results demonstrate that this technique provides a noticeable reduction in processing time and better quality of the reconstructed image compared to other, previously employed techniques, such as point or fringe scanning, or even other known space encoding techniques.