Dynamic Vertical Mapping with Crowdsourced Smartphone Sensor Data

Pipelidis, Georgios; Rad, Omid Reza Moslehi; Iwaszczuk, D.; Prehofer, Christian; Hugentobler, Urs

doi:10.3390/s18020480

Cited by 7 publications

(6 citation statements)

References 21 publications

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“…It is usually integrated with other sensors, like inertial sensors [69,82], environmental sensors (light, temperature, sound, etc.) [109,110], location-based sensors (GPS) [71,96], and communication infrastructure (WiFi, Bluetooth, RFID, etc.) [72,73,100,110].…”

Section: Applications: Multi-sensor Studiesmentioning

confidence: 99%

On the Challenges and Potential of Using Barometric Sensors to Track Human Activity

Manivannan

Chin

Barrat

et al. 2020

Sensors

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Barometers are among the oldest engineered sensors. Historically, they have been primarily used either as environmental sensors to measure the atmospheric pressure for weather forecasts or as altimeters for aircrafts. With the advent of microelectromechanical system (MEMS)-based barometers and their systematic embedding in smartphones and wearable devices, a vast breadth of new applications for the use of barometers has emerged. For instance, it is now possible to use barometers in conjunction with other sensors to track and identify a wide range of human activity classes. However, the effectiveness of barometers in the growing field of human activity recognition critically hinges on our understanding of the numerous factors affecting the atmospheric pressure, as well as on the properties of the sensor itself—sensitivity, accuracy, variability, etc. This review article thoroughly details all these factors and presents a comprehensive report of the numerous studies dealing with one or more of these factors in the particular framework of human activity tracking and recognition. In addition, we specifically collected some experimental data to illustrate the effects of these factors, which we observed to be in good agreement with the findings in the literature. We conclude this review with some suggestions on some possible future uses of barometric sensors for the specific purpose of tracking human activities.

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Section: Applications: Multi-sensor Studiesmentioning

confidence: 99%

On the Challenges and Potential of Using Barometric Sensors to Track Human Activity

Manivannan

Chin

Barrat

et al. 2020

Sensors

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“…In their solution, multiple barometers were installed in the building to provide reference pressure values. Pipelidis et al [ 47 ] proposed a dynamic vertical mapping system using crowdsourced sensor measurements.…”

Section: Solution Background and Related Workmentioning

confidence: 99%

Grid-Based Bayesian Filtering Methods for Pedestrian Dead Reckoning Indoor Positioning Using Smartphones

Opiela

Galčík

2020

Sensors

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Indoor positioning systems for smartphones are often based on Pedestrian Dead Reckoning, which computes the current position from the previously estimated location. Noisy sensor measurements, inaccurate step length estimations, faulty direction detections, and a demand on the real-time calculation introduce the error which is suppressed using a map model and a Bayesian filtering. The main focus of this paper is on grid-based implementations of Bayes filters as an alternative to commonly used Kalman and particle filters. Our previous work regarding grid-based filters is elaborated and enriched with convolution mask calculations. More advanced implementations, the centroid grid filter, and the advanced point-mass filter are introduced. These implementations are analyzed and compared using different configurations on the same raw sensor recordings. The evaluation is performed on three sets of experiments: a custom simple path in faculty building in Slovakia, and on datasets from IPIN competitions from a shopping mall in France, 2018 and a research institute in Italy, 2019. Evaluation results suggests that proposed methods are qualified alternatives to the particle filter. Advantages, drawbacks and proper configurations of these filters are discussed in this paper.

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“…only storey geometry and basic details), there is an extended selection of approaches given the lower requirements for the amount of detail and accuracy. Some methods include: predicting the basic interior from the exterior geometry and other information (Boeters et al, 2015;Loch-Dehbi et al, 2017) and crowdsourced sensor data from smartphones (barometric sensors and WiFi positioning) (Pipelidis et al, 2018;Tuncer et al, 2017).…”

Section: Floorplans In 3d Gis and Their Acquisitionmentioning

confidence: 99%

Floor Plans in Citygml

Konde

Tauscher

Biljecki

et al. 2018

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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<p><strong>Abstract.</strong> This paper (1) discusses the modelling of floor plans in CityGML; (2) proposes a delineation of multiple variants of indoor LoD0 in line with the current proposal for CityGML 3.0; (3) demonstrates a method to generate CityGML datasets with included floor plans; and (4) explores their usability. The use of an Application Domain Extension (ADE) is being proposed in order to preserve potentially useful information found within detailed building information models (BIM), specifically Industry Foundation Class (IFC), that cannot be stored in CityGML natively. Our work follows the current developments of CityGML 3.0, and based on the discussions in the CityGML Standards Working Group (SWG) it showcases one of the first datasets consistent with the ongoing development of CityGML 3.0 and one that follows the proposals for a new LOD concept and new interior features.</p>

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Dynamic Vertical Mapping with Crowdsourced Smartphone Sensor Data

Cited by 7 publications

References 21 publications

On the Challenges and Potential of Using Barometric Sensors to Track Human Activity

On the Challenges and Potential of Using Barometric Sensors to Track Human Activity

Grid-Based Bayesian Filtering Methods for Pedestrian Dead Reckoning Indoor Positioning Using Smartphones

Floor Plans in Citygml

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