Reliability or Sustainability

Kartakis, Sokratis; Yang, Shusen; McCann, Julie A.

doi:10.1145/3064840

Cited by 6 publications

(4 citation statements)

References 28 publications

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“…Most studies tried to improve groundwater use efficiency using smart solutions (Fornarelli et al, 2022). The remaining 15 studies considered other ecosystems, such as wetlands (Mahdianpari et al, 2021), lakes (Maleki et al, 2022), mountains (Gilliom et al, 2019), and rivers (Kartakis et al, 2017).…”

Section: Water-related Ecosystems (T6)mentioning

confidence: 99%

Scientometric Review of Smart Water Management Literature From the Sustainable Development Goal Perspective

Bao,

Martek,

et al. 2023

International Journal of Strategic Property Management

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Water is essential to human survival; however, many people, particularly those in poorer countries, lack access to reliable sources of clean and safe water. Despite decades of effort to address this issue, water sustainability remains elusive even today. Smart technologies have been widely adopted for water management, rendering smart water management a promising path to achieving water sustainability. Nevertheless, the efficacy of such smart water management in attaining sustainability remains unclear. This study aims to investigate the progress made in pursuing water sustainability with smart water management through a scientometric literature review. The Scopus database was employed to extract a pool of 460 candidate publications, which were then analyzed for content using bibliometric analysis and VOSviewer software. Nine clustered research themes were classified, corresponding to the nine targets of sustainable development goals (SDGs) for water. The findings show that engagement across these topics is highly unequal, providing substantial guidance on where emerging research efforts should be concentrated. The novelty of this study mainly lies in the SDG perspective that provides a significant but overlooked angle for observing progress in smart water management domain. The findings can enlighten the international water industry to create a more favorable environment for regions lagging in using smart technologies to facilitate overall water sustainability.

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Section: Water-related Ecosystems (T6)mentioning

confidence: 99%

Scientometric Review of Smart Water Management Literature From the Sustainable Development Goal Perspective

Bao,

Martek,

et al. 2023

International Journal of Strategic Property Management

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“…Likewise, the Markov model for the reliability analysis of sensor nodes in wireless sensor networks was proposed in [3]. Similarly, the use of the stochastic optimization problem to maximize estimation reliability in water distribution networks was suggested in [50]. The quantification of the reliability of grid splitting under degraded communication conditions in the presence of cyber interdependencies was presented in [51].…”

Section: Reliability Of Sensors In Cyber-physicals Systems a Brief Smentioning

confidence: 99%

Sensor Reliability in Cyber-Physical Systems Using Internet-of-Things Data: A Review and Case Study

et al. 2019

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Nowadays, reliability of sensors is one of the most important challenges for widespread application of Internet-of-things data in key emerging fields such as the automotive and manufacturing sectors. This paper presents a brief review of the main research and innovation actions at the European level, as well as some on-going research related to sensor reliability in cyber-physical systems (CPS). The research reported in this paper is also focused on the design of a procedure for evaluating the reliability of Internet-of-Things sensors in a cyber-physical system. The results of a case study of sensor reliability assessment in an autonomous driving scenario for the automotive sector are also shown. A co-simulation framework is designed in order to enable real-time interaction between virtual and real sensors. The case study consists of an IoT LiDAR-based collaborative map in order to assess the CPS-based co-simulation framework. Specifically, the sensor chosen is the Ibeo Lux 4-layer LiDAR sensor with IoT added capabilities. The modeling library for predicting error with machine learning methods is implemented at a local level, and a self-learning-procedure for decision-making based on Q-learning runs at a global level. The study supporting the experimental evaluation of the co-simulation framework is presented using simulated and real data. The results demonstrate the effectiveness of the proposed method for increasing sensor reliability in cyber-physical systems using Internet-of-Things data.

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“…There has also been an increasing interest in the image reconstruction of the in-pipe environment, where detection methods, such as process tomography [32,33], are becoming more mainstream. As of today, many innovative wireless sensor networks for pipeline systems emphasize the failure response time, efficiency of computation and the reliability of the communication systems used [14,[34][35][36][37][38][39][40]. By having a combination of physical pipeline networks, sensing capabilities and computational elements, wireless sensor networks for the detection of defects in pipelines are essentially part of the family of cyber-physical systems.…”

Section: Introductionmentioning

confidence: 99%

“…Figure37. Solid model of a screw-drive robot, which is capable of moving along the x-axis, y-axis and z-axis in straight and curved pipelines.…”

mentioning

confidence: 99%

Failure Detection Methods for Pipeline Networks: From Acoustic Sensing to Cyber-Physical Systems

Wong

McCann

2021

Sensors

Self Cite

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Pipeline networks have been widely utilised in the transportation of water, natural gases, oil and waste materials efficiently and safely over varying distances with minimal human intervention. In order to optimise the spatial use of the pipeline infrastructure, pipelines are either buried underground, or located in submarine environments. Due to the continuous expansion of pipeline networks in locations that are inaccessible to maintenance personnel, research efforts have been ongoing to introduce and develop reliable detection methods for pipeline failures, such as blockages, leakages, cracks, corrosion and weld defects. In this paper, a taxonomy of existing pipeline failure detection techniques and technologies was created to comparatively analyse their respective advantages, drawbacks and limitations. This effort has effectively illuminated various unaddressed research challenges that are still present among a wide array of the state-of-the-art detection methods that have been employed in various pipeline domains. These challenges include the extension of the lifetime of a pipeline network for the reduction of maintenance costs, and the prevention of disruptive pipeline failures for the minimisation of downtime. Our taxonomy of various pipeline failure detection methods is also presented in the form of a look-up table to illustrate the suitability, key aspects and data or signal processing techniques of each individual method. We have also quantitatively evaluated the industrial relevance and practicality of each of the methods in the taxonomy in terms of their respective deployability, generality and computational cost. The outcome of the evaluation made in the taxonomy will contribute to our future works involving the utilisation of sensor fusion and data-centric frameworks to develop efficient, accurate and reliable failure detection solutions.

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Reliability or Sustainability

Cited by 6 publications

References 28 publications

Scientometric Review of Smart Water Management Literature From the Sustainable Development Goal Perspective

Scientometric Review of Smart Water Management Literature From the Sustainable Development Goal Perspective

Sensor Reliability in Cyber-Physical Systems Using Internet-of-Things Data: A Review and Case Study

Failure Detection Methods for Pipeline Networks: From Acoustic Sensing to Cyber-Physical Systems

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