Zobrazeno 1 - 10
of 112
pro vyhledávání: '"Till, Riedel"'
Autor:
Giannis Ioannidis, Paul Tremper, Chaofan Li, Till Riedel, Nikolaos Rapkos, Christos Boikos, Leonidas Ntziachristos
Publikováno v:
Atmosphere, Vol 15, Iss 9, p 1056 (2024)
Assessing air quality in urban areas is vital for protecting public health, and low-cost sensor networks help quantify the population’s exposure to harmful pollutants effectively. This paper introduces an innovative method to calibrate air-quality
Externí odkaz:
https://doaj.org/article/8e911f75f92c491faba1cb8fe3eccad2
Autor:
Andreas Wierse, Till Riedel
Wenn in Datenbergen wertvolle Geheimnisse schlummern, aus denen Profit erzielt werden soll, dann geht es um Big Data. Doch wie schöpft man aus »großen Daten« echte Werte, wenn man nicht gerade Google ist? Um aus Unternehmens-, Maschinen- oder Sen
Publikováno v:
Atmosphere, Vol 15, Iss 1, p 113 (2024)
Health factors concerning the well-being of the urban population urge us to better comprehend the impact of emissions in urban environments on the micro-scale. There is great necessity to depict and monitor pollutant concentrations with high precisio
Externí odkaz:
https://doaj.org/article/5083fb8061a8452a8e195dc1aba756b8
Autor:
Markus Lucking, Niclas Kannengieber, Maurice Kilgus, Till Riedel, Michael Beigl, Ali Sunyaev, Wilhelm Stork
Publikováno v:
IEEE Access, Vol 8, Pp 189365-189381 (2020)
Pollution-monitoring systems (PMSs) are used worldwide to sense environmental changes, such as air quality conditions or temperature increases, and to monitor compliance with regulations. However, organizations manage the environmental data collected
Externí odkaz:
https://doaj.org/article/92551e838cb2410581c0487ec66f858f
Publikováno v:
at - Automatisierungstechnik. 70:767-776
The enormous potential of artificial intelligence, especially artificial neural networks, when used for edge computing applications in cars, traffic lights or smart watches, has not yet been fully exploited today. The reasons for this are the computi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::67342c7a802902241f28b423a2967ae2
https://doi.org/10.1515/auto-2022-0023
https://doi.org/10.1515/auto-2022-0023
Publikováno v:
Neural Information Processing ISBN: 9783031301100
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2383ea48fd2c447f65438addf10e7990
https://doi.org/10.1007/978-3-031-30111-7_18
https://doi.org/10.1007/978-3-031-30111-7_18
Publikováno v:
Machine Learning and Knowledge Discovery in Databases ISBN: 9783031264085
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8878bec27bd92b4bf9d94dce2cbe5223
https://doi.org/10.1007/978-3-031-26409-2_35
https://doi.org/10.1007/978-3-031-26409-2_35
Autor:
Anja Bachmann, Robert Zetzsche, Andrea Schankin, Till Riedel, Michael Beigl, Markus Reichert, Philip Santangelo, Ulrich Ebner-Priemer
Publikováno v:
EAI Endorsed Transactions on Ambient Systems, Vol 3, Iss 12, Pp 1-4 (2015)
In ambulatory assessment, psychologists apply experience sampling methods (ESM) on mobile devices to assess self-reports from subjects. One major challenge is to support domain experts to create ESM apps themselves without prior programming knowledge
Externí odkaz:
https://doaj.org/article/661e9a48692f44bcaac22761a33024d0
Autor:
Nicolaie L. Fantana, Till Riedel, Jochen Schlick, Stefan Ferber, Jürgen Hupp, Stephen Miles, Florian Michahelles, Stefan Svensson
Publikováno v:
Internet of Things ISBN: 9781003338659
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::266ae28a86a7210d88e72f25aa964524
https://doi.org/10.1201/9781003338659-3
https://doi.org/10.1201/9781003338659-3
Publikováno v:
Sensors, Vol 19, Iss 3, p 749 (2019)
Precise, location-specific fine dust measurement is central for the assessment of urban air quality. Classic measurement approaches require dedicated hardware, of which professional equipment is still prohibitively expensive (>10k$) for dense measure
Externí odkaz:
https://doaj.org/article/04a93c7e06574932a9a654f3c42ed50f