Fundamental aspects in sensor network metrology

Eichstädt, Sascha; Vedurmudi, Anupam Prasad; Gruber, Maximilian; Hutzschenreuter, Daniel

doi:10.21014/actaimeko.v12i1.1417

Cited by 9 publications

(5 citation statements)

References 15 publications

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“…The metrological assessment of sensor networks necessitates a fundamental revision of calibration, uncertainty propagation and performance assessment and new approaches for information and data handling regarding the individual sensors and their interactions in the network to allow a systems metrology approach to be established. The contribution by Sascha Eichstädt et al [4] introduces some initial findings from recent research and gives an outlook into future developments.…”

Section: Dear Readersmentioning

confidence: 99%

Introductory notes for the Acta IMEKO first issue 2023, Special issue on metrology and digital transformation

Bartholomew

Hutzschenreuter

Prugovečki³

et al. 2023

Acta IMEKO

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Section: Dear Readersmentioning

confidence: 99%

Introductory notes for the Acta IMEKO first issue 2023, Special issue on metrology and digital transformation

Bartholomew

Hutzschenreuter

Prugovečki³

et al. 2023

Acta IMEKO

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show abstract

“…Researchers and engineers continually work on developing advanced calibration techniques, robust sensor designs, and sophisticated data processing algorithms to address these metrological limitations. As sensor networks become increasingly integral to various fields, from smart cities to industrial automation, overcoming these challenges is essential to unlocking the full potential of these interconnected systems [54][55][56][57][58].…”

Section: Sensor Network Metrological Limitationsmentioning

confidence: 99%

Sensing Systems in Construction and the Built Environment: Review, Prospective, and Challenges

Malekmohammadi,

Farzadnia,

Hajrasouliha

et al. 2023

Sensors

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This article is a comprehensive review of state-of-the-art sensors of the built environment, applicable in construction, structural engineering, management, and planning industries. This review is framed within the technical definition of sensing systems and their components. Existing sensors are listed and described in two broad categories of structural health monitoring (SHM) and building environment monitoring (BEM). The SHM systems are used for monitoring the long-term performance of structures, such as bridges and buildings. BEM systems are employed to ensure the safety and comfort of the built environment’s occupants, as well as the general monitoring of the environment for any required maintenance. The applications and implementation challenges of both systems are discussed, with emphasis on common sensing system limitations such as energy supply, packaging, network layout, and performance validation. Finally, the prospect of sensing systems as part of a digital twin that incorporates multifunctional sophisticated monitoring systems and intelligent analysis methods is discussed.

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“…In order to enhance the monitoring and control of air pollution, governments and related entities have deployed high-precision reference stations in critical areas, but rising costs and high maintenance have prevented intensive deployment. In recent years, low-cost sensor arrays (LCSAs), consisting of low-cost target pollutants sensors and other sensors such as temperature, humidity [2][3][4][5] and other gases that are cross-sensitive to the target pollutants [4][5][6], have been applied in urban concentration monitoring due to their low price, removability and maintenancefree characteristics [7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

The development of a meta-learning calibration network for low-cost sensors across domains

Tianliang,

Xingchuang,

Shangzhong

2023

Metrology and Measurement Systems

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Low-cost sensor arrays are an economical and efficient solution for large-scale networked monitoring of atmospheric pollutants. These sensors need to be calibrated in situ before use, and existing data-driven calibration models have been widely used, but require large amounts of co-location data with reference stations for training, while performing poorly across domains. To address this problem, a meta-learningbased calibration network for air sensors is proposed, which has been tested on ozone datasets. The tests have proved that it outperforms five other conventional methods in important metrics such as mean absolute error, root mean square error and correlation coefficient. Taking Manlleu and Tona as the source domain and Vic as the target domain, the proposed method reduces MAE and RMSE by 17.06% and 6.71% on average, and improves R2 by an average of 4.21%, compared with the suboptimal pre-trained multi-source transfer calibration. The method can provide a new idea and direction to solve the problem of cross-domain and reliance on a large amount of co-location data in the calibration of sensors.

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Fundamental aspects in sensor network metrology

Cited by 9 publications

References 15 publications

Introductory notes for the Acta IMEKO first issue 2023, Special issue on metrology and digital transformation

Introductory notes for the Acta IMEKO first issue 2023, Special issue on metrology and digital transformation

Sensing Systems in Construction and the Built Environment: Review, Prospective, and Challenges

The development of a meta-learning calibration network for low-cost sensors across domains

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