Metrics and Methods to Assess Building Fault Detection and Diagnosis Tools

Frank, Stephen; Lin, Guanjing; Jin, Xin; Singla, Rupam; Farthing, Amanda; Liang, Zhang; Granderson, Jessica

doi:10.2172/1503166

Cited by 9 publications

(6 citation statements)

References 28 publications

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“…This section presents the result of these interviews, followed by a discussion of the impact of evaluation procedure choices on evaluation outcomes and on data set generation. Additional methodology concerning these expert interviews is documented in [51].…”

Section: Discussionmentioning

confidence: 99%

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A performance evaluation framework for building fault detection and diagnosis algorithms

Frank¹,

Lin²,

Jin³

et al. 2019

Energy and Buildings

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Fault detection and diagnosis (FDD) algorithms for building systems and equipment represent one of the most active areas of research and commercial product development in the buildings industry. However, far more e↵ort has gone into developing these algorithms than into assessing their performance. As a result, considerable uncertainties remain regarding the accuracy and e↵ectiveness of both research-grade FDD algorithms and commercial products-a state of a↵airs that has hindered the broad adoption of FDD tools. This article presents a general, systematic framework for evaluating the performance of FDD algorithms. The article focuses on understanding the possible answers to two key questions: in the context of FDD algorithm evaluation, what defines a fault and what defines an evaluation input sample? The answers to these questions, together with appropriate performance metrics, may be used to fully specify evaluation procedures for FDD algorithms.

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Section: Discussionmentioning

confidence: 99%

“…For example, the true positive rate is the proportion of positive fault cases that are correctly identified as such. For a more comprehensive discussion of performance metrics including conceptual illustrations, full mathematical definitions, and a survey of technically advanced metrics, refer to [51].…”

Section: Evaluation Outcomesmentioning

confidence: 99%

A performance evaluation framework for building fault detection and diagnosis algorithms

Frank¹,

Lin²,

Jin³

et al. 2019

Energy and Buildings

Self Cite

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“…• 0 -If no smoke detected. Based on the abovementioned outcomes, following metrics can be used for evaluation [37,[45][46][47]:…”

Section: • Garbage Values If Unhealthymentioning

confidence: 99%

SWOT: A Hybrid Hardware-Based Approach for Robust Fault-Tolerant Framework in a Smart Day Care

Sharma¹,

Gupta

et al. 2022

Security and Communication Networks

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Internet of Things (IoT) has made its imprint on every part of the globe today. Offices, households, factories, industries, agriculture, and day cares, among other places, have all upgraded to their innovative version. It has propounded great potential in various real-world applications. The topical trends in the adoption of IoT have also highlighted the challenges associated with the performance of IoT devices. IoT devices require continuous monitoring for any performance degradation. A bibliometric analysis of 587 papers is undertaken on the Scopus database to spot the increasing interest of researchers in fault detection in IoT. A smart system’s or an IoT-based space’s usability, efficiency, and performance are all built on a fault-tolerant approach and interruption-free smooth operations. The investigation was carried out based on the literature to determine the need for a pro-fault detection system in an IoT-enabled day care. Kids’ security and safety are highly dependent on the hassle-free working of smart devices. It’s overhead to carry out device tracking manually along with demanding kids. This issue needs to be addressed to uphold the smart day care’s trustworthiness. A pro-fault detection approach can be applied to resolve the aforementioned issue to enhance the smart day care’s performance and efficiency. This paper proposes SWOT, a novel hybrid hardware-based approach in an IoT-based day care to safeguard the proper working of all IoT devices deployed. It screens every single appliance associated with a smart day care to detect the faulty appliance beforehand. The solution will assist the day care staff in providing the best care and security to their kids without any overhead. SWOT evaluation proved that it is an economical and efficient approach in detecting faults, accurately, swiftly, and with a low false alarm ratio.

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“…Performance metrics for any fault detection technique verify how good the technique is. A confusion matrix [119,[151][152][153][154] can be taken as the basis for evaluating the outcomes of a faultdetecting technique as given away in Fig. 14.…”

Section: Metrics For Evaluation Of Fault Detection Techniquesmentioning

confidence: 99%

An Insight Survey on Sensor Errors and Fault Detection Techniques in Smart Spaces

Sharma,

Gupta,

Gupta

et al. 2024

CMES

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The widespread adoption of the Internet of Things (IoT) has transformed various sectors globally, making them more intelligent and connected. However, this advancement comes with challenges related to the effectiveness of IoT devices. These devices, present in offices, homes, industries, and more, need constant monitoring to ensure their proper functionality. The success of smart systems relies on their seamless operation and ability to handle faults. Sensors, crucial components of these systems, gather data and contribute to their functionality. Therefore, sensor faults can compromise the system's reliability and undermine the trustworthiness of smart environments. To address these concerns, various techniques and algorithms can be employed to enhance the performance of IoT devices through effective fault detection. This paper conducted a thorough review of the existing literature and conducted a detailed analysis. This analysis effectively links sensor errors with a prominent fault detection technique capable of addressing them. This study is innovative because it paves the way for future researchers to explore errors that have not yet been tackled by existing fault detection methods. Significant, the paper, also highlights essential factors for selecting and adopting fault detection techniques, as well as the characteristics of datasets and their corresponding recommended techniques. Additionally, the paper presents a methodical overview of fault detection techniques employed in smart devices, including the metrics used for evaluation. Furthermore, the paper examines the body of academic work related to sensor faults and fault detection techniques within the domain. This reflects the growing inclination and scholarly attention of researchers and academicians toward strategies for fault detection within the realm of the Internet of Things.

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Metrics and Methods to Assess Building Fault Detection and Diagnosis Tools

Cited by 9 publications

References 28 publications

A performance evaluation framework for building fault detection and diagnosis algorithms

A performance evaluation framework for building fault detection and diagnosis algorithms

SWOT: A Hybrid Hardware-Based Approach for Robust Fault-Tolerant Framework in a Smart Day Care

An Insight Survey on Sensor Errors and Fault Detection Techniques in Smart Spaces

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