Gabriel de Blasio

Study on an Indoor Positioning System for Harsh Environments Based on Wi-Fi and Bluetooth Low Energy

This paper presents a study of positioning system that provides advanced information services based on Wi-Fi and Bluetooth Low Energy (BLE) technologies. It uses Wi-Fi for rough positioning and BLE for fine positioning. It is designed for use in public transportation system stations and terminals where the conditions are “hostile” or unfavourable due to signal noise produced by the continuous movement of passengers and buses, data collection conducted in the constant presence thereof, multipath fading, non-line of sight (NLOS) conditions, the fact that part of the wireless communication infrastructure has already been deployed and positioned in a way that may not be optimal for positioning purposes, variable humidity conditions, etc. The ultimate goal is to provide a service that may be used to assist people with special needs. We present experimental results based on scene analysis; the main distance metric used was the Euclidean distance but the Mahalanobis distance was also used in one case. The algorithm employed to compare fingerprints was the weighted k-nearest neighbor one. For Wi-Fi, with only three visible access points, accuracy ranged from 3.94 to 4.82 m, and precision from 5.21 to 7.0 m 90% of the time. With respect to BLE, with a low beacon density (1 beacon per 45.7 m2), accuracy ranged from 1.47 to 2.15 m, and precision from 1.81 to 3.58 m 90% of the time. Taking into account the fact that this system is designed to work in real situations in a scenario with high environmental fluctuations, and comparing the results with others obtained in laboratory scenarios, our results are promising and demonstrate that the system would be able to position users with these reasonable values of accuracy and precision.

Systems methods in visual modelling

Models of visual processing in living systems can be successfully developed for the front end sensorial part, which in vertebrates correspond to the retina. The appropriate modelling tools are the tools of classical systems theory. In this line, we present first analytical models for the frogs retina and for higher vertebrate retinae, leading to the generalized structure of receptive fields processing for modelling linear and non-linear behaviour. Next, transformations on input data receptive fields are presented, including the novel concept of micro-structures of retinal receptive fields in form of Newton Filters, the concepts of transformation on input and output spaces and the concepts of transformation on receptive fields by means of partitions.

Systems and Computational Tools for Neuronal Retinal Models

This paper presents some systems theoretical and computational tools which allow for qualitative and quantitative models to explain the rate of firing (outputs) of ganglion retinal cells to various stimuli, mostly in higher vertebrates. Section 1 presents the neurophysiological bases of the formal tools, in which the main point is that specialized computation by some ganglion cells is to be performed at the inner plexiform layer, via amacrines. Section 2, presents the minima prerequisites for a qualitative model of linear and non-linear behavior of ganglia for higher vertebrates. The points here are that signals reaching the inner plexiform layer are fast and retarded versions of the input image, and that non-linear local lateral interaction accounts for non-linearities. Section 3, is devoted to computational representations that will permit to go from qualitative to quantitative formal models. The computational tools are based on generalized Newton Filters.

Analysis of Distance and Similarity Metrics in Indoor Positioning Based on Bluetooth Low Energy.

In this work, we provide an analysis of BLE channel-separate fingerprinting using different distance and similarity measures. In a 168 m\(^{2}\) testbed, 12 beacons with Eddystone and iBeacon protocols set were deployed, taking into account the orientation of users and considering 10 distance/similarity measures. We have observed that there is an orientation that offers the best positioning performance with the combination of iBeacon protocol, channel 38 and Mahalanobis distance. Taking 8 samples in the online phase, accuracy values obtained are in the range 1.28 m–1.88 m, and precision values are within 1.90 m–3.76 m or less, 90% of the time and depending which orientation the observer is facing.

Ubiquitous Signaling System for Public Road Transport Network

Mobility is a basic need for people, therefore the authorities in advanced societies pay special attention to systems and initiatives that improve or facilitate it. In this work, a ubiquitous signaling system for visually impaired people, using a combination of WiFi and Bluetooth Low Energy (BLE) technology with Smart Mobile Devices, is proposed. The system is conceived as a solution to help and support these users in places of public road transportation with travellers massive transit, such as bus stations, interchangers or preferred stops. In addition, once the user is positioned in the desired location, the system would offer advanced services: information on lines schedules, tickets sale, etc.

Bioinspired computing nets for directionality in vision

Directional selectivity to local visual stimuli appears in various levels of the visual pathway, being in the retina very conspicuous. Neurophysiology suggests that directionality (as well as other local and quasi-global filtering properties) are based in the space–time interactions of processes with different “memory” (latency). We draw inspiration from the corresponding underlying biological mechanisms to propose two general schemes for directionality computation in nets, compatible with other space–time filtering properties. First, a connectivistic mechanism based on bipolar–amacrine–ganglion cell interaction is proposed, by formalizing the classical proposals of early vision neurophysiologists. Second, inspired initially in the more recently described intrinsic directionality of amacrines, novel schemes are proposed where directionality appear as the computing consequence of adding memory to spatial filtering structures. The mathematical formulations are achieved by means of Newton Filters and Hermite Functionals.

New biomimetic neural structures for artificial neural nets

The general aim is to formalize known properties of real neurons, formulating them into appropriate mathematical models. These will converge into, hopefully, more powerful neurophysiological founded distributed computation units of artificial neural nets. Redundancy and distributed computation are key factors to be embodied in the corresponding biomimetic structures. We focus in two neurophysiological processes: first, the dendro-dendritic or afferent non linear interactions, prior to the synapses with the cell body. Computational redundancy (and reliability as a consequence) is to be expected. Second, distributed computation, also provoked by a dendritic-like computational structure to generate arbitrary receptive fields weights or profiles, where also, a kind of reliability is expected, result of the distributed nature of the computation.

Local Space-Time Systems Simulation of Linear and Non-linear Retinal Processes

The realization of local space-time models of retinal processes can be achieved by means of available typical dynamical systems simulation tools (like Simulink) because only a very small number of parallel channels is needed. In short, the aim is to simulate both the time and space dimensions as delay chains, where the travelling signals are available at different points of the delay chain to interact among them. These models provide an interesting and fruitful insight into the neurophysiological processes.

Using Data Mining to Analyze Dwell Time and Nonstop Running Time in Road-Based Mass Transit Systems

Travel Time plays a key role in the quality of service in road-based mass transit systems. In this type of mass transit systems, travel time of a public transport line is the sum of the dwell time at each bus stop and the nonstop running time between pair of consecutives bus stops of the line. The aim of the methodology presented in this paper is to obtain the behavior patterns of these times. Knowing these patterns, it would be possible to reduce travel time or its variability to make more reliable travel time predictions. To achieve this goal, the methodology uses data related to check-in and check-out movements of the passengers and vehicles GPS positions, processing this data by Data Mining techniques. To illustrate the validity of the proposal, the results obtained in a case of use in presented.

Study of Dynamic Factors in Indoor Positioning for Harsh Environments

This paper presents a study of the impact of dynamic factors on indoor positioning. A positioning system is presented that provides advanced information services based on two subsystems: Wi-Fi and Bluetooth Low Energy (BLE). The first subsystem was intended to position users with not very high levels of accuracy and precision, but not too far from reality, and the second one was intended to position users with greater precision. It is designed for use in stations and terminals of public transportation systems in which the conditions are “hostile” or unfavourable. Experimental results demonstrate that, using different devices for both offline and online phase, RSS differences, Euclidean distance and comparing fingerprints with Weighted k-Nearest Neighbours (WKNN) algorithm, the system is able to position users with reasonable values of accuracy and precision: for Wi-Fi, with only 3 samples, depending on the orientation and compared with 3 neighbours, an average accuracy between 4.15 and 4.58 m and a precision in the range 4–7 m or less 90% of the time were obtained; for BLE, best accuracy results were obtained by comparison with 2 neighbours, giving a position error of 1.59 m and a CDF value of 2.83 m or less 90% of the time.