Indoor localization for pedestrians with real-time capability using multi-sensor smartphones

ABSTRACT

The localization of persons or objects usually refers to a position determined in a spatial reference system. Outdoors, this is usually accomplished with Global Navigation Satellite Systems (GNSS). However, the automatic positioning of people in GNSS-free environments, especially inside of buildings (indoors) poses a huge challenge. Indoors, satellite signals are attenuated, shielded or reflected by building components (e.g. walls or ceilings). For selected applications, the automatic indoor positioning is possible based on different technologies (e.g. WiFi, RFID, or UWB). However, a standard solution is still not available. Many indoor positioning systems are only suitable for specific applications or are deployed under certain conditions, e.g. additional infrastructures or sensor technologies. Smartphones, as popular cost-effective multi-sensor systems, is a promising indoor localization platform for the mass-market and is increasingly coming into focus. Today’s devices are equipped with a variety of sensors that can be used for indoor positioning. In this contribution, an approach to smartphone-based pedestrian indoor localization is presented. The novelty of this approach refers to a holistic, real-time pedestrian localization inside of buildings based on multi-sensor smartphones and easy-to-install local positioning systems. For this purpose, the barometric altitude is estimated in order to derive the floor on which the user is located. The 2D position is determined subsequently using the principle of pedestrian dead reckoning based on user's movements extracted from the smartphone sensors. In order to minimize the strong error accumulation in the localization caused by various sensor errors, additional information is integrated into the position estimation. The building model is used to identify permissible (e.g. rooms, passageways) and impermissible (e.g. walls) building areas for the pedestrian. Several technologies contributing to higher precision and robustness are also included. For the fusion of different linear and non-linear data, an advanced algorithm based on the Sequential Monte Carlo method is presented.     

A model for the viscosity of rhyolite as a function of H2O-content and pressure: A calibration based on centrifuge piston cylinder experiments

The Newtonian viscosity of synthetic rhyolitic liquids with 0.15-5.24 wt% dissolved water was determined in the interval between 580 and 1640 °C and pressures of 1 atm and 5-25 kbar. Measurements were performed by combining static and accelerated (up to 1000g) falling sphere experiments on water-bearing samples, with high temperature concentric cylinder experiments on 0.15 wt% H₂O melts. These methods allowed viscosity determinations between 10² and 10⁷ Pa s, and cover the complete range of naturally occurring magmatic temperatures, pressures, and H₂O-contents for rhyolites.Our viscosity data, combined with those from previous studies, were modeled by an expression based on the empirical Vogel-Fulcher-Tammann equation, which describes viscosities and derivative properties (glass transition temperature T_g, fragility m, and activation volume of viscous flow Va) of silicic liquids as a function of P-T-X_(H2O). The fitted expressions do not account for composition-dependent parameters other than X_(H2O) and reproduce the entire viscosity database for silicic liquids to within 3.0% average relative error on log η (i.e. std. error of estimate of 0.26 log units).The results yield the expected strong decrease of viscosity with temperature and water content, but show variable pressure dependencies. Viscosity results to be strongly affected by pressure at low pressures; an effect amplified at low temperatures and water contents. Fragility, as a measure for the deviation from Arrhenian behavior, decreases with H₂O-content but is insensitive to pressure. Activation volumes are always largely negative (e.g., less than −10 cm³/mol) and increase strongly with H₂O-content. Variations in melt structure that may account for the observed property variations are discussed.     

Total content and chemical speciation of arsenic in the polychaete Sabella spallanzanii

An unusual feature has been observed in polychaetes regarding their capacity to accumulate high levels of relatively toxic forms of arsenic in specific tissues. Basal levels of arsenic and distribution of its compounds were investigated in tissues of the Mediterranean polychaete Sabella spallanzanii. Particularly high concentrations were measured in the branchial crown (1036+/-136 microg/g d.w.) and chemical speciation revealed that the predominant form was the relatively toxic dimethylarsinate (DMA). These data suggest a potential role of As as anti-predatory strategy in polychaetes.     

Estimation of daily stream water temperatures with a Bayesian regression approach

Stream water temperature plays a significant role in aquatic ecosystems where it controls many important biological and physical processes. Reliable estimates of water temperature at the daily time step are critical in managing water resources. We developed a parsimonious piecewise Bayesian model for estimating daily stream water temperatures that account for temporal autocorrelation and both linear and nonlinear relationships with air temperature and discharge. The model was tested at 8 climatically different basins of the USA and at 34 sites within the mountainous Boise River Basin (Idaho, USA). The results show that the proposed model is robust with an average root mean square error of 1.25 °C and Nash–Sutcliffe coefficient of 0.92 over a 2‐year period. Our approach can be used to predict historic daily stream water temperatures in any location using observed daily stream temperature and regional air temperature data.     

Ressi experimental catchment: Ecohydrological research in the Italian pre-Alps

Ressi is a small (2.4 ha) forested catchment located in the Italian pre-Alps. The site became an experimental catchment to investigate the water fluxes in the soil–plant–atmosphere continuum and the impact of vegetation on runoff generation in 2012. The elevation of the catchment ranges from 598 to 721 m a.s.l. and the climate is humid temperate. The bedrock consists of rhyolites and dacites; the soil is a Cambisol. The catchment is covered by a dense forest, dominated by beech, chestnut, maple, and hazel trees. The field set up includes measurements of the rainfall in an open area, streamflow at the outlet, soil moisture at various depths and locations, and depth to water table in six piezometers at a 5- or 10-min interval. Samples of precipitation, stream water, shallow groundwater and soil water are collected monthly for tracer analysis (stable isotopes (²H and ¹⁸O), electrical conductivity and major ions), and during selected rainfall–runoff events to determine the contribution of the various sources to runoff. Since 2017, soil and plant water samples have been collected to determine the sources of tree transpiration. Data collected in the period 2012–2016 are publicly available. Data collection is ongoing, and the data set is expected to be updated on an annual basis to include the most recent measurements.     

In situ high-temperature X-ray diffraction and spectroscopic study of fibroferrite,FeOH(SO<Subscript>4</Subscript>)·5H<Subscript>2</Subscript>O

The thermal dehydration process of fibroferrite, FeOH(SO₄)·5H₂O, a secondary iron-bearing hydrous sulfate, was investigated by in situ high-temperature synchrotron X-ray powder diffraction (HT-XRPD), in situ high-temperature Fourier transform infrared spectroscopy (HT-FTIR) and thermal analysis (TGA-DTA) combined with evolved gas mass spectrometry. The data analysis allowed the determination of the stability fields and the reaction paths for this mineral as well as characterization of its high-temperature products. Five main endothermic peaks are observed in the DTA curve collected from room T up to 800 °C. Mass spectrometry of gases evolved during thermogravimetric analysis confirms that the first four mass loss steps are due to water emission, while the fifth is due to a dehydroxylation process; the final step is due to the decomposition of the remaining sulfate ion. The temperature behavior of the different phases occurring during the heating process was analyzed, and the induced structural changes are discussed. In particular, the crystal structure of a new phase, FeOH(SO₄)·4H₂O, appearing at about 80 °C due to release of one interstitial H₂O molecule, was solved by ab initio real-space and reciprocal-space methods. This study contributes to further understanding of the dehydration mechanism and thermal stability of secondary sulfate minerals.     

Using a regional numerical weather prediction model for GNSS positioning over Brazil

The global navigation satellite system (GNSS) can provide centimeter positioning accuracy at low costs. However, in order to obtain the desired high accuracy, it is necessary to use high-quality atmospheric models. We focus on the troposphere, which is an important topic of research in Brazil where the tropospheric characteristics are unique, both spatially and temporally. There are dry regions, which lie mainly in the central part of the country. However, the most interesting area for the investigation of tropospheric models is the wet region which is located in the Amazon forest. This region substantially affects the variability of humidity over other regions of Brazil. It provides a large quantity of water vapor through the humidity convergence zone, especially for the southeast region. The interconnection and large fluxes of water vapor can generate serious deficiencies in tropospheric modeling. The CPTEC/INPE (Center for Weather Forecasting and Climate Studies/Brazilian Institute for Space Research) has been providing since July 2012 a numerical weather prediction (NWP) model for South America, known as Eta. It has yield excellent results in weather prediction but has not been used in GNSS positioning. This NWP model was evaluated in precise point positioning (PPP) and network-based positioning. Concerning PPP, the best positioning results were obtained for the station SAGA, located in Amazon region. Using the NWP model, the 3D RMS are less than 10 cm for all 24 h of data, whereas the values reach approximately 60 cm for the Hopfield model. For network-based positioning, the best results were obtained mainly when the tropospheric characteristics are critical, in which case an improvement of up to 7.2 % was obtained in 3D RMS using NWP models.     

Long-term monitoring of the behavior of a talus-colluvium deposit

Landslides - This article describes the behavior of a talus-colluvium deposit up to 70-m thick located in the Serra dos Orgaos, Rio de Janeiro/RJ, Brazil. The monitoring dataset of 13 years...     

Chromium(VI) reduction by sulphur(IV) in aqueous solutions

The rates of the reduction of Cr(VI) with S(IV) were measured in deaerated NaCl solution as a function of pH, temperature and ionic strength. The rates of the reaction were found to be first order with respect to Cr(VI) and second order with respect to S(IV), in agreement with previous results obtained at concentrations two order higher than the present study. The reaction also showed a first-order dependence of the rates on the concentration of the proton and a small influence of temperature with an apparent energy of activation ΔH_app of 22.8 ± 3.4 kJ/mol. The rates were independent of ionic strength from 0.01 to 1 M. The rate of Cr(VI) reduction is described by the general expression

−d[Cr(VI)]/dt=k[Cr(VI)][S(IV)]²