المؤلفون: Traboulsi, Salam, Knauth, Stefan

المصدر: iCity. Transformative Research for the Livable, Intelligent, and Sustainable City ; page 307-314 ; ISBN 9783030920951 9783030920968

الوصف: Indoor temperature is one of the fundamental features of the indoor environment. It can be controlled with distributed IoT sensors, through wireless networks. It affects human indoor environment such as human thermal sensation, productivity at work, buildings’ quality, and several syndrome symptoms. In this study, we focus on the effects of the indoor temperature on the human work productivity and thermal sensation. Our research aims to develop an IoT monitoring tool to manage the challenges in smart buildings by extracting and processing relevant data. It proposes data analysis periodically and integrates newly generated data into the analytical cycle that allows improving human indoor environment.

الإتاحة: https://doi.org/10.1007/978-3-030-92096-8_20Test

المؤلفون: Renaudin, Valerie, Potortì, Francesco, Torres-Sospedra, Joaquín, Knauth, Stefan, O’keefe, Kyle, Park, Chan Gook, Sugimoto, Masanori, Wei, Dongyan, Nurmi, Jari

المساهمون: Tampere University, Electrical Engineering

مصطلحات موضوعية: 213 Electronic, automation and communications engineering, electronics

الوصف: Indoor localization is a growing research field and interest is expanding in many application fields, including services, measurement, mapping, security, and standardization. The quest for appropriate tracking technologies for COVID-19 pandemic control has shown us the importance of identifying the sensors data and processing that are suitable, accurate, reliable, and respectful of privacy. A prominent area is, therefore, that of sensors, where both improved hardware solutions and more powerful data analysis are required. ; Non peer reviewed

وصف الملف: fulltext

العلاقة: 22; Bibtex: 9733819; ORCID: /0000-0003-2169-4606/work/111129623; https://trepo.tuni.fi/handle/10024/138564Test; URN:NBN:fi:tuni-202204073102

الإتاحة: https://doi.org/10.1109/JSEN.2022.3150130Test
https://trepo.tuni.fi/handle/10024/138564Test

المؤلفون: Mendoza-Silva, Germán Martín, Torres-Sospedra, Joaquín, Potortì, Francesco, Moreira, Adriano, Knauth, Stefan, Berkvens, Rafael, Huerta, Joaquin

مصطلحات موضوعية: error measurement, indoor pathfinding, indoor positioning system (IPS) evaluation, Wi-Fi fingerprinting

الوصف: Indoor positioning systems (IPSs) suffer from a lack of standard evaluation procedures enabling credible comparisons: this is one of the main challenges hindering their widespread market adoption. Traditionally, accuracy evaluation is based on positioning errors defined as the Euclidean distance between the true positions and the estimated positions. While Euclidean is simple, it ignores obstacles and floor transitions. In this article, we describe procedures that measure a positioning error defined as the length of the pedestrian path that connects the estimated position to the true position. The procedures apply pathfinding on floor maps using visibility graphs (VGs) or navigational meshes (NMs) for vector maps and fast marching (FM) for raster maps. Multifloor and multibuilding paths use the information on vertical in-building communication ways and outdoor paths. The proposed measurement procedures are applied to position estimates provided by the IPSs that participated in the EvAAL-ETRI 2015 competition. Procedures are compared in terms of pedestrian path realism, indoor model complexity, path computation time, and error magnitudes. The VGs algorithm computes shortest distance paths; NMs produce very similar paths with significantly shorter computation time; and FM computes longer, more natural-looking paths at the expense of longer computation time and memory size. The 75th percentile of the measured error differs among the methods from 2.2 to 3.7 m across the evaluation sets.

وصف الملف: application/pdf

العلاقة: IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, VOL. 70, 2021; https://ieeexplore.ieee.org/document/9186638Test; MENDOZA-SILVA, Germán Martín, et al. Beyond Euclidean Distance for Error Measurement in Pedestrian Indoor Location. IEEE Transactions on Instrumentation and Measurement, 2020, vol. 70, p. 1-11.; http://hdl.handle.net/10234/191365Test; https://doi.org/10.1109/TIM.2020.3021514Test

الإتاحة: https://doi.org/10.1109/TIM.2020.3021514Test
http://hdl.handle.net/10234/191365Test

المؤلفون: Mendoza-Silva, German Martin, Torres-Sospedra, Joaquin, Potorti, Francesco, Moreira, Adriano, Knauth, Stefan, Berkvens, Rafael, Huerta, Joaquin

المصدر: 0018-9456 ; IEEE transactions on instrumentation and measurement

مصطلحات موضوعية: Physics, Engineering sciences. Technology

الوصف: Indoor positioning systems (IPSs) suffer from a lack of standard evaluation procedures enabling credible comparisons: this is one of the main challenges hindering their widespread market adoption. Traditionally, accuracy evaluation is based on positioning errors defined as the Euclidean distance between the true positions and the estimated positions. While Euclidean is simple, it ignores obstacles and floor transitions. In this article, we describe procedures that measure a positioning error defined as the length of the pedestrian path that connects the estimated position to the true position. The procedures apply pathfinding on floor maps using visibility graphs (VGs) or navigational meshes (NMs) for vector maps and fast marching (FM) for raster maps. Multifloor and multibuilding paths use the information on vertical in-building communication ways and outdoor paths. The proposed measurement procedures are applied to position estimates provided by the IPSs that participated in the EvAAL-ETRI 2015 competition. Procedures are compared in terms of pedestrian path realism, indoor model complexity, path computation time, and error magnitudes. The VGs algorithm computes shortest distance paths; NMs produce very similar paths with significantly shorter computation time; and FM computes longer, more natural-looking paths at the expense of longer computation time and memory size. The 75th percentile of the measured error differs among the methods from 2.2 to 3.7 m across the evaluation sets.

العلاقة: info:eu-repo/semantics/altIdentifier/isi/000594910700016

الإتاحة: https://doi.org/10.1109/TIM.2020.3021514Test
https://hdl.handle.net/10067/1713830151162165141Test
https://repository.uantwerpen.be/docstore/d:irua:2079Test

المؤلفون: Schnee, Laura S., Knauth, Stefan, Hapca, Simona, Otten, Wilfred, Eickhorst, Thilo

المصدر: Plant and Soil, 2016 Nov 01. 408(1/2), 357-368.

الوصول الحر: http://www.jstor.org/stable/44136962Test

المؤلفون: Renaudin, Valerie, Ortiz, Miguel, Perul, Johan, Torres-Sospedra, Joaquin, Ramon Jimenez, Antonio, Perez-Navarro, Antoni, Martin Mendoza-Silva, German, Seco, Fernando, Landau, Yael, Marbel, Revital, Ben-Moshe, Boaz, Zheng, Xingyu, Ye, Feng, Kuang, Jian, Li, Yu, Niu, Xiaoji, Landa, Vlad, Hacohen, Shlomi, Shvalb, Nir, Lu, Chuanhua, Uchiyama, Hideaki, Thomas, Diego, Shimada, Atsushi, Taniguchi, Rin-Ichiro, Ding, Zhenxing, Xu, Feng, Kronenwett, Nikolai, Vladimirov, Blagovest, Lee, Soyeon, Cho, Eunyoung, Jun, Sungwoo, Lee, Changeun, Park, Sangjoon, Lee, Yonghyun, Rew, Jehyeok, Park, Changjun, Jeong, Hyeongyo, Han, Jaeseung, Lee, Keumryeol, Zhang, Wenchao, Li, Xianghong, Wei, Dongyan, Zhang, Ying, Park, So Young, Park, Chan Gook, Knauth, Stefan, Pipelidis, Georgios, Tsiamitros, Nikolaos, Lungenstrass, Tomas, Pablo Morales, Juan, Trogh, Jens, Plets, David, Opiela, Miroslav, Fang, Shih-Hau, Tsao, Yu, Chien, Ying-Ren, Yang, Shi-Shen, Ye, Shih-Jyun, Ali, Muhammad Usman, Hur, Soojung, Park, Yongwan

المصدر: IEEE ACCESS ; ISSN: 2169-3536

مصطلحات موضوعية: Technology and Engineering, SIMULTANEOUS LOCALIZATION, SLAM, IPIN, competition, indoor positioning, smartphone

الوصف: 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.

وصف الملف: application/pdf

العلاقة: https://biblio.ugent.be/publication/8647948Test; http://hdl.handle.net/1854/LU-8647948Test; http://dx.doi.org/10.1109/ACCESS.2019.2944389Test; https://biblio.ugent.be/publication/8647948/file/8648624Test

الإتاحة: https://doi.org/10.1109/ACCESS.2019.2944389Test
https://biblio.ugent.be/publication/8647948Test
http://hdl.handle.net/1854/LU-8647948Test
https://biblio.ugent.be/publication/8647948/file/8648624Test

المؤلفون: Traboulsi, Salam, Knauth, Stefan

الوصف: The indoor air temperature is one of the key factors to improve the performance of energy efficiency of buildings and quality of life in a very smart IoT environment. Therefore, a periodic and accurate prediction of the minimum and maximum indoor air temperature allows taking necessary precautions to handle the variations’ impact and tendencies. During this assessment, we developed minimum and maximum indoor air temperature prediction models using multiple statistical regression (MLR), multilayered perceptron (MLP), and random forest (RF, where Rf is achieved once with tree depth 10 (RFdepth10), and once with tree depth 50 (RFdepth50)). The study was conducted at a building located within the University of Applied Sciences, Stuttgart, in Germany. Sensors were accustomed to aggregate data, which were used because of the input variables for the prediction. The variables are outdoor air temperature, indoor air temperature, humidity, and heating temperature. Performance of the models was evaluated with the coefficient of determination and therefore the root means square error (RMSE). The simulation results showed that the prediction by the MLP algorithm, based on minimum indoor air temperature models and also maximum indoor air temperature models, provides better accuracy with the very best and lowest RMSE in the independent test dataset. This survey developed a straightforward and powerful MLP model to predict the minimum and therefore the maximum indoor air temperature, which may integrate into smart building management system technology in the future.

العلاقة: https://opus.bsz-bw.de/hft/frontdoor/index/index/docId/482Test

الإتاحة: https://opus.bsz-bw.de/hft/frontdoor/index/index/docId/482Test

المؤلفون: Torres-Sospedra, Joaquín, Jiménez Ruiz, Antonio Ramón, Moreira, Adriano, Lungenstrass, Tomás, Lu, Wei-Chung, Knauth, Stefan, Mendoza Silva, Germán Martín, Seco, Fernando, Perez-Navarro, Antoni, Nicolau, Maria João, Costa, António, Meneses, Filipe, Farina, Joaquín, Morales, Juan Pablo, Lu, Wen-Chen, Cheng, Ho-Ti, Yang, Shi-Shen, Fang, Shih-Hau, Chien, Ying-Ren, Tsao, Yu

مصطلحات موضوعية: Indoor positioning and navigation, Wi-Fi fingerprinting, Sensor fusion, Competitions, Benchmarking, Cellular telephone systems, Telefonia mòbil, Teléfono móvil

الوصف: The development of indoor positioning solutions using smartphones is a growing activity with an enormous potential for everyday life and professional applications. The research activities on this topic concentrate on the development of new positioning solutions that are tested in specific environments under their own evaluation metrics. To explore the real positioning quality of smartphone-based solutions and their capabilities for seamlessly adapting to different scenarios, it is needed to find fair evaluation frameworks. The design of competitions using extensive pre-recorded datasets is a valid way to generate open data for comparing the different solutions created by research teams. In this paper, we discuss the details of the 2017 IPIN indoor localization competition, the different datasets created, the teams participating in the event, and the results they obtained. We compare these results with other competition-based approaches (Microsoft and Perf-loc) and on-line evaluation web sites. The lessons learned by organising these competitions and the benefits for the community are addressed along the paper. Our analysis paves the way for future developments on the standardization of evaluations and for creating a widely-adopted benchmark strategy for researchers and companies in the field.

وصف الملف: application/pdf

العلاقة: https://www.mdpi.com/1424-8220/18/2/487/pdfTest; Torres Sospedra, J., Jiménez, A., Moreira, A., Lungenstrass, T., Lu, W.-C., Knauth, S., Mendoza Silva, G.M., Seco, F., Pérez Navarro, A., Nicolau, M.J., Costa, A., Meneses, F., Farina, J., Morales, J.P., Lu, W.-C., Cheng, H.-T., Yang, S.-S., Fang, S.-H., Chien, Y.-R. & Tsao, Y. (2018). Off-Line Evaluation of Mobile-Centric Indoor Positioning Systems: The Experiences from the 2017 IPIN Competition. Sensors, 18(2), 1-27. doi:10.3390/s18020487; http://hdl.handle.net/10609/93682Test

الإتاحة: https://doi.org/10.3390/s18020487Test
http://hdl.handle.net/10609/93682Test

المؤلفون: Torres-Sospedra, Joaquín, Moreira, Adriano, Knauth, Stefan, Berkvens, Rafael, Montoliu, Raul, Belmonte, Oscar, Trilles, Sergio, Nicolau, Maria João, Meneses, Filipe, Costa, António, Koukofikis, Athanasios, Weyn, Maarten, Peremans, Herbert

مصطلحات موضوعية: Wi-Fi Fingerprinting, Off-site competition, Indoor positioning, Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática, Science & Technology

الوصف: Pre-print version ; This paper presents results from comparing different Wi-Fi fingerprinting algorithms on the same private dataset. The algorithms where realized by independent teams in the frame of the off-site track of the EvAAL-ETRI Indoor Localization Competition which was part of the Sixth International Conference on Indoor Positioning and Indoor Navigation (IPIN 2015). Competitors designed and validated their algorithms against the publicly available UJIIndoorLoc database which contains a huge reference- and validation data set. All competing systems were evaluated using the mean error in positioning, with penalties, using a private test dataset. The authors believe that this is the first work in which Wi-Fi fingerprinting algorithm results delivered by several independent and competing teams are fairly compared under the same evaluation conditions. The analysis also comprises a combined approach: Results indicate that the competing systems where complementary, since an ensemble that combines three competing methods reported the overall best results. ; We would like to thank Francesco Potortì, Paolo Barsocchi, Michele Girolami and Kyle O’Keefe for their valuable help in organizing and spread the EVAALETRI competition and the off-site track. We would also like to thank the TPC members Machaj Juraj, Christos Laoudias, Antoni Pérez-Navarro and Robert Piché for their valuable comments, suggestions and reviews. Parts of this work were funded in the frame of the Spanish Ministry of Economy and Competitiveness through the “Metodologiías avanzadas para el diseño, desarrollo, evaluación e integración de algoritmos de localización en interiores” project (Proyectos I+D Excelencia, código TIN2015-70202-P) and the “Red de Posicionamiento y Navegación en Interiores” network (Redes de Excelencia, código TEC2015-71426- REDT). Parts of this work were funded in the frame of the German federal Ministry of Education and Research programme "FHprofUnt2013" under contract 03FH035PB3 (Project SPIRIT). ...

وصف الملف: application/pdf

العلاقة: http://content.iospress.com/articles/journal-of-ambient-intelligence-and-smart-environments/ais421Test; Joaquín Torres-Sospedra, Adriano Moreira, Stefan Knauth, Rafael Berkvens, Raul Montoliu, Oscar Belmonte, Sergio Trilles, Maria João Nicolau, Filipe Meneses, António Costa, Athanasios Koukofikis, Maarten Weyn and Herbert Peremans, “A Realistic Evaluation of Indoor Positioning Systems Based on Wi-Fi Fingerprinting: The 2015 EvAAL-ETRI Competition”, in the Journal of Ambient Intelligence and Smart Environments, 2017.; http://hdl.handle.net/1822/46108Test

الإتاحة: https://doi.org/10.3233/AIS-170421Test
http://hdl.handle.net/1822/46108Test

المؤلفون: Torres-Sospedra, Joaquín, Jiménez, Antonio R., Knauth, Stefan, Moreira, Adriano, Beer, Yair, Fetzer, Toni, Viet-Cuong Ta, Nicolau, Maria João, Costa, António, Meneses, Filipe

مصطلحات موضوعية: Indoor localization technology, Indoor navigation, Smartphone applications, Evaluation and benchmarking, Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática, Science & Technology

الوصف: This paper presents the analysis and discussion of the off-site localization competition track, which took place during the Seventh International Conference on Indoor Positioning and Indoor Navigation (IPIN 2016). Five international teams proposed different strategies for smartphone-based indoor positioning using the same reference data. The competitors were provided with several smartphone-collected signal datasets, some of which were used for training (known trajectories), and others for evaluating (unknown trajectories). The competition permits a coherent evaluation method of the competitors' estimations, where inside information to fine-tune their systems is not offered, and thus provides, in our opinion, a good starting point to introduce a fair comparison between the smartphone-based systems found in the literature. The methodology, experience, feedback from competitors and future working lines are described. ; We would like to thank Tecnalia Research & Innovation Foundation for sponsoring the competition track with an award for the winning team. We are also grateful to Francesco Potortì, Sangjoon Park, Jesús Ureña and Kyle O’Keefe for their invaluable help in promoting the IPIN competition and conference. Parts of this work was carried out with the financial support received from projects and grants: LORIS (TIN2012-38080-C04-04), TARSIUS (TIN2015-71564-C4-2-R (MINECO/FEDER)), SmartLoc (CSIC-PIE Ref.201450E011), “Metodologías avanzadas para el diseño, desarrollo, evaluación e integración de algoritmos de localización en interiores” (TIN2015-70202-P), REPNIN network (TEC2015-71426-REDT) and the José Castillejo mobility grant (CAS16/00072). The HFTS team has been supported in the frame of the German Federal Ministry of Education and Research programme “FHprofUnt2013” under contract 03FH035PB3 (Project SPIRIT). The UMinho team has been supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT — Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2013. ...

وصف الملف: application/pdf

العلاقة: info:eu-repo/grantAgreement/FCT/5876/147280/PT; http://www.mdpi.com/1424-8220/17/3/557/htmTest; Torres-Sospedra, Joaquín, et al. "The Smartphone-Based Offline Indoor Location Competition at IPIN 2016: Analysis and Future Work." Sensors 17.3 (2017): 557; http://hdl.handle.net/1822/46107Test

الإتاحة: https://doi.org/10.3390/s17030557Test
http://hdl.handle.net/1822/46107Test