Evaluating indoor positioning systems in a shopping mall : the lessons learned from the IPIN 2018 competition

The Indoor Positioning and Indoor Navigation (IPIN) conference holds an annual competition in which indoor localization systems from different research groups worldwide are evaluated empirically. The objective of this competition is to establish a systematic evaluation methodology with rigorous metrics both for real-time (on-site) and post-processing (off-site) situations, in a realistic environment unfamiliar to the prototype developers. For the IPIN 2018 conference, this competition was held on September 22nd, 2018, in Atlantis, a large shopping mall in Nantes (France). Four competition tracks (two on-site and two off-site) were designed. They consisted of several 1 km routes traversing several floors of the mall. Along these paths, 180 points were topographically surveyed with a 10 cm accuracy, to serve as ground truth landmarks, combining theodolite measurements, differential global navigation satellite system (GNSS) and 3D scanner systems. 34 teams effectively competed. The accuracy score corresponds to the third quartile (75th percentile) of an error metric that combines the horizontal positioning error and the floor detection. The best results for the on-site tracks showed an accuracy score of 11.70 m (Track 1) and 5.50 m (Track 2), while the best results for the off-site tracks showed an accuracy score of 0.90 m (Track 3) and 1.30 m (Track 4). These results showed that it is possible to obtain high accuracy indoor positioning solutions in large, realistic environments using wearable light-weight sensors without deploying any beacon. This paper describes the organization work of the tracks, analyzes the methodology used to quantify the results, reviews the lessons learned from the competition and discusses its future

Usporedba zrcalnog modela i modela prijenosnih linija u analizi horizontalne žičane strukture iznad dvoslojnog tla

The paper presents comparison between two approximate models of energized horizontal thin-wire conductors above two-layer soil. The formulation is posed in frequency domain by using two approaches. The first one is based on quasi-static image theory within Mixed Potential Integral Equation. The second one is based on transmission line theory with approximation of per unit length parameters. The authors compare currents computed by the both approximate models of a center fed wire to establish the computation errors over a wide frequency range. The main objective is to validate the proposed image and transmission line models for various lengths of wire conductors, and various cases of low and high conductivities of two-layer soil. The verification of the results is done by comparison with exact model based on full-wave theory. Detailed parametric analysis clearly illustrate validity domain and problems when using both approximate models with respect to their use in practical EMC studies.U radu je prikazana usporedba dviju približnih modela analize pobuđenog horizontalnog tankog žičanog vodiča iznad dvoslojnog tla. Formulacija problema je izvedena u frekvencijskoj domeni pomoću dva pristupa. Prvi pristup se temelji na kvazi-statičkom zrcalnom modelu unutar integralne jednadžbe s mješovitim potencijalima. Drugi se temelji na teoriji prijenosnih linija s aproksimacijom jediničnih parametara. Autori su usporedili distribucije struje izračunate s pomoću obje približne metode kako bi odredili pogrešku metoda u širokom rasponu frekvencija. Glavni cilj bio je potvrditi predloženi zrcalni i linijski model za različite duljine žičanog vodiča i razne slučajeve niske i visoke vodljivosti slojeva tla. Provjera rezultata obavljena je usporedbom s modelom bez aproksimacija temeljenog na punovalnoj teoriji. Detaljna parametarska analiza jasno pokazuju valjanosti domene i vrste problema uz korištenje obje približne metode s obzirom na njihovu primjenu u praktičnim EMC razmatranjima

Pedestrian Flow Identification and Occupancy Prediction for Indoor Areas

Indoor localization is used to locate objects and people within buildings where outdoor tracking tools and technologies cannot provide precise results. This paper aims to improve analytics research, focusing on data collected through indoor localization methods. Smart devices recurrently broadcast automatic connectivity requests. These packets are known as Wi-Fi probe requests and can encapsulate various types of spatiotemporal information from the device carrier. In addition, in this paper, we perform a comparison between the Prophet model and our implementation of the autoregressive moving average (ARMA) model. The Prophet model is an additive model that requires no manual effort and can easily detect and handle outliers or missing data. In contrast, the ARMA model may require more effort and deep statistical analysis but allows the user to tune it and reach a more personalized result. Second, we attempted to understand human behaviour. We used historical data from a live store in Dubai to forecast the use of two different models, which we conclude by comparing. Subsequently, we mapped each probe request to the section of our place of interest where it was captured. Finally, we performed pedestrian flow analysis by identifying the most common paths followed inside our place of interest

Distributed Generation Control Using Ripple Signaling and a Multiprotocol Communication Embedded Device

Remotely performing real-time distributed generation control and a demand response is a basic aspect of the grid ancillary services provided by grid operators, both the transmission grid operators (TSOs) and distribution grid operators (DNOs), in order to ensure that voltage, frequency and power loads of the grid remain within safe limits. The stochastic production of electrical power to the grid from the distributed generators (DGs) from renewable energy sources (RES) in conjunction with the newly appeared stochastic demand consumers (i.e., electric vehicles) hardens the efforts of the DNOs to keep the grid’s operation within safe limits and prevent cascading blackouts while staying in compliance with the SAIDI and SAIFI indices during repair and maintenance operations. Also taking into consideration the aging of the existing grid infrastructure, and making it more prone to failure year by year, it is yet of great significance for the DNOs to have access to real-time feedback from the grid’s infrastructure—which is fast, has low-cost upgrade interventions, is easily deployed on the field and has a fast response potential—in order to be able to perform real-time grid management (RTGM). In this article, we present the development and deployment of a control system for DG units, with the potential to be installed easily to TSO’s and DNO’s substations, RES plants and consumers (i.e., charging stations of electric vehicles). This system supports a hybrid control mechanism, either via ripple signaling or through a network, with the latter providing real-time communication capabilities. The system can be easily installed on the electric components of the grid and can act as a gateway between the different vendors communication protocols of the installed electrical equipment. More specifically, a commercially available, low-cost board (Raspberry Pi) and a ripple control receiver are installed at the substation of a PV plant. The board communicates in real-time with a remote server (decision center) via a 5G modem and with the PV plants inverters via the Modbus protocol, which acquires energy production data and controls the output power of each inverter, while one of its digital inputs can be triggered by the ripple control receiver. The ripple control receiver receives on-demand signals with the HEDNO, triggering the digital input on the board. When the input is triggered, the board performs a predefined control command (i.e., lower the inverter’s power output to 50%). The board can also receive control commands directly from the remote server. The remote server receives real-time feedback of the acquired inverter data, the control signals from the ripple control receiver and the state and outcome of each performed control command