Abstract
veracity) for sensor data. Traditional signal processing approaches are no longer sufficient, requiring combined approaches in both architectural and analytical layers. This paper proposes a discussion on the adequate foundations of a new
general approach aimed at increasing robustness and antifragility of IoT-based smart applications. In addition, it shows results of preliminary experiments with real data in the context of precision irrigation using multivariate methods to
identify relevant situations, such as sensor failures and the mismatch of contextual sensor information due to different spatial granularities capture. Our results provide initial indications of the adequacy of the proposed framework.
Original language | English |
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Title of host publication | IEEE LATINCOM 2019 Conference Proceedings |
Publisher | IEEE Institute of Electrical and Electronic Engineers |
Number of pages | 6 |
Publication status | Accepted/In press - 13 Nov 2019 |
MoE publication type | A4 Article in a conference publication |
Event | IEEE Latin-American Conference on Communications - Salvador, Brazil Duration: 11 Nov 2019 → 13 Nov 2019 |
Conference
Conference | IEEE Latin-American Conference on Communications |
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Country | Brazil |
City | Salvador |
Period | 11/11/19 → 13/11/19 |
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Foundations of Data Quality Assurance for IoT-based Smart Applications. / Tognieri, Rodrigo; Camponogara, Glauber; Soininen, Juha-Pekka; Kamienski, Carlos.
IEEE LATINCOM 2019 Conference Proceedings. IEEE Institute of Electrical and Electronic Engineers , 2019.Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review
TY - GEN
T1 - Foundations of Data Quality Assurance for IoT-based Smart Applications
AU - Tognieri, Rodrigo
AU - Camponogara, Glauber
AU - Soininen, Juha-Pekka
AU - Kamienski, Carlos
PY - 2019/11/13
Y1 - 2019/11/13
N2 - Most current scientific and industrial efforts in IoT are geared towards building integrated platforms to finally realize its potential in commercial scale applications. The IoT and Big Data contemporary context brings a number of challenges, such as providing quality assurance (defined by availability andveracity) for sensor data. Traditional signal processing approaches are no longer sufficient, requiring combined approaches in both architectural and analytical layers. This paper proposes a discussion on the adequate foundations of a newgeneral approach aimed at increasing robustness and antifragility of IoT-based smart applications. In addition, it shows results of preliminary experiments with real data in the context of precision irrigation using multivariate methods toidentify relevant situations, such as sensor failures and the mismatch of contextual sensor information due to different spatial granularities capture. Our results provide initial indications of the adequacy of the proposed framework.
AB - Most current scientific and industrial efforts in IoT are geared towards building integrated platforms to finally realize its potential in commercial scale applications. The IoT and Big Data contemporary context brings a number of challenges, such as providing quality assurance (defined by availability andveracity) for sensor data. Traditional signal processing approaches are no longer sufficient, requiring combined approaches in both architectural and analytical layers. This paper proposes a discussion on the adequate foundations of a newgeneral approach aimed at increasing robustness and antifragility of IoT-based smart applications. In addition, it shows results of preliminary experiments with real data in the context of precision irrigation using multivariate methods toidentify relevant situations, such as sensor failures and the mismatch of contextual sensor information due to different spatial granularities capture. Our results provide initial indications of the adequacy of the proposed framework.
M3 - Conference article in proceedings
BT - IEEE LATINCOM 2019 Conference Proceedings
PB - IEEE Institute of Electrical and Electronic Engineers
ER -