The Use of Group Decision-Making to Improve the Monitoring of Air Quality

Orłowski, Cezary; Cofta, Piotr; Wąsik, Mariusz; Welfler, Piotr; Pastuszka, Józef S.

doi:10.1007/978-3-662-60555-4_9

Cited by 5 publications

(6 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The implementation of the proposition may rely on the central processing, where all sensors report their measurements to the central database, and a specific piece of software ("sensor agent") issues opinions on behalf of them. This is the implementation assumed by this paper, and it is the implementation of the actual network [32].…”

Section: Special Cases and Architectural Notesmentioning

confidence: 99%

Trust-Based Model for the Assessment of the Uncertainty of Measurements in Hybrid IoT Networks

Cofta

Orłowski

Lebiedź

2020

Sensors

Self Cite

View full text Add to dashboard Cite

The aim of this paper is to introduce a NUT model (NUT: network-uncertainty-trust) that aids the decrease of the uncertainty of measurements in autonomous hybrid Internet of Things sensor networks. The problem of uncertainty in such networks is a consequence of various operating conditions and varied quality of measurement nodes, making statistical approach less successful. This paper presents a model for decreasing the uncertainty through the use of socially inspired metaphors of reputation, trust, and confidence that are the untapped latent information. The model described in the paper shows how the individual reputation of each node can be assessed on the basis of opinions provided by other nodes of the hybrid measurement network, and that this method allows to assess the extent of uncertainty the node introduces to the network. This, in turn, allows nodes of low uncertainty to have a greater impact on the reconstruction of values. The verification of the model, as well as examples of its applicability to air quality measurements are presented as well. Simulations demonstrate that the use of the model can decrease the uncertainty by up to 55% while using the EWMA (exponentially weighted moving average) algorithm, as compared to the reference one.

show abstract

Section: Special Cases and Architectural Notesmentioning

confidence: 99%

Trust-Based Model for the Assessment of the Uncertainty of Measurements in Hybrid IoT Networks

Cofta

Orłowski

Lebiedź

2020

Sensors

Self Cite

View full text Add to dashboard Cite

show abstract

“…For the sake of illustration, let us consider the example of the same citizen network that has been introduced early in this paper [ 1 ]. The model presented in this paper can help with the systematic identification of uncertainties that have to be dealt with, and with the most important research that should be done.…”

Section: Case Studymentioning

confidence: 99%

“…Let us consider citizen IoT networks that measure the level of air pollution such as the one described in [ 1 ]. These networks have been using some popular IoT protocols, mostly out of the COTS (commercial off-the-shelf) components.…”

Section: Introductionmentioning

confidence: 99%

“…Referring back to the case of the IoT sensor networks [ 1 ], the authors determined, for example, that while the uncertainty introduced by sensors is acceptable, its key challenges lie in the long-term behavior of the sensors, specifically in the impact of the lack of reference measurements, calibration protocols and regular maintenance. Furthermore, increase in network-level uncertainty relates to longer term disconnection resulting from volunteers forgetting about the installation.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Conceptual Model of Measurement Uncertainty in IoT Sensor Networks

Cofta

Karatzas

Orłowski

2021

Sensors

Self Cite

View full text Add to dashboard Cite

The growing popularity of inexpensive IoT (Internet of Things) sensor networks makes their uncertainty an important aspect of their adoption. The uncertainty determines their fitness for purpose, their perceived quality and the usefulness of information they provide. Nevertheless, neither the theory nor the industrial practice of uncertainty offer a coherent answer on how to address uncertainty of networks of this type and their components. The primary objective of this paper is to facilitate the discussion of what progress should be made regarding the theory and the practice of uncertainty of IoT sensor networks to satisfy current needs. This paper provides a structured overview of uncertainty, specifically focusing on IoT sensor networks. It positions IoT sensor networks as contrasted with professional measurement and control networks and presents their conceptual sociotechnical reference model. The reference model advises on the taxonomy of uncertainty proposed in this paper that demonstrates semantic differences between various views on uncertainty. This model also allows for identifying key challenges that should be addressed to improve the theory and practice of uncertainty in IoT sensor networks.

show abstract

“…The Continuous Improvement process model was developed based on the research experiment carried out as well as on the basis of the analysis of functionalities necessary for the design of IoT systems (Orłowski, 2018(Orłowski, , 2019. This model takes into account two areas (Figure 11): the area of design environment and the area of functionality of IoT systems.…”

Section: Continuous Improvement Process Modelmentioning

confidence: 99%