Combining contaminant event diagnosis with data validation/reconstruction: Application to smart buildings

Cugueró, Miquel A.; Christodoulou, Marinos; Quevedo, Joseba; Puig, Vicenç; García, Dominie; Michaelides, Michalis P.

doi:10.1109/med.2014.6961386

Cited by 3 publications

(1 citation statement)

References 15 publications

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“…While data validation is important for improving the reliability of a system, it also depends on other factors, such as power instability, temperature changes, out-of-range data, internal and external noises, and synchronization problems that occur when multiple sensors are integrated into a system [2]. However, the reconstruction of the data and correction for the correct measurement is also important, and several research studies have proposed systems, methods, models, and frameworks to improve the data validation and reconstruction [3,4].…”

Section: Data Validation Methodsmentioning

confidence: 99%

Validation Techniques for Sensor Data in Mobile Health Applications

et al. 2016

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Mobile applications have become a must in every user’s smart device, and many of these applications make use of the device sensors’ to achieve its goal. Nevertheless, it remains fairly unknown to the user to which extent the data the applications use can be relied upon and, therefore, to which extent the output of a given application is trustworthy or not. To help developers and researchers and to provide a common ground of data validation algorithms and techniques, this paper presents a review of the most commonly used data validation algorithms, along with its usage scenarios, and proposes a classification for these algorithms. This paper also discusses the process of achieving statistical significance and trust for the desired output.

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Section: Data Validation Methodsmentioning

confidence: 99%

Validation Techniques for Sensor Data in Mobile Health Applications

et al. 2016

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Sensor Data Validation and Reconstruction

Quevedo¹,

García²,

Puig³

et al. 2017

Advances in Industrial Control

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A methodology and a software tool for sensor data validation/reconstruction: Application to the Catalonia regional water network

Escofet

García

Quevedo

et al. 2016

Control Engineering Practice

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In this paper, a sensor data validation/reconstruction methodology applicable to water networks and its implementation by means of a software tool, are presented. The aim is to guarantee that the sensor data are reliable and complete in case that sensor faults occur. The availability of such dataset is of paramount importance in order to successfully use the sensor data for further tasks e.g. water billing, network efficiency assessment, leak localisation and real-time operational control. The methodology presented here is based on a sequence of tests and on the combined use of spatial models (SM) and time series models (TSM) applied to the sensors used for real-time monitoring and control of the water network. Spatial models take advantage of the physical relations between different system variables (e.g. flow and level sensors in hydraulic systems) while time series models take advantage of the temporal redundancy of the measured variables (here by means of a Holt-Winters (HW) time series model). First, the data validation approach, based on several tests of different complexity, is described to detect potential invalid or missing data. Then, the reconstruction process is based on a set of spatial and time series models used to reconstruct the missing/invalid data with the model estimation providing the best fit. A software tool implementing the proposed data validation and reconstruction methodology is also described. Finally, results obtained applying the proposed methodology to a real case study based on the Catalonia regional water network is used to illustrate its performance.

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Combining contaminant event diagnosis with data validation/reconstruction: Application to smart buildings

Cited by 3 publications

References 15 publications

Validation Techniques for Sensor Data in Mobile Health Applications

Validation Techniques for Sensor Data in Mobile Health Applications

Sensor Data Validation and Reconstruction

A methodology and a software tool for sensor data validation/reconstruction: Application to the Catalonia regional water network

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