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Quality Assurance

Quality Assurance

Quality assurance is the overarching term used to describe the activities employed to ensure the proper performance of a system. These activities can be classified into three categories: quality control, quality assessment, and internal corrective measures. Typically, these activities work cyclically: quality control is performed before and during the analysis, while quality assessment occurs during and after the investigation. Internal corrective measures are implemented based on the findings...

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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

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Safety Integrity Level (SIL) assessment process for WSN using multi-QoS metrics.

Sivasubramanian Srinivasan¹, T K Ramesh¹, Roberto Paccapeli²

¹Department of Electronics and Communication Engineering, Amrita School of Engineering, Bengaluru, Amrita Vishwa Vidyapeetham India.

|October 28, 2025

Summary

This summary is machine-generated.

This study introduces a new method for assessing the safety of industrial Wireless Sensor Networks (WSN). It uses multiple Quality of Service (QoS) metrics to ensure compliance with safety integrity levels (SIL) for critical industrial applications.

Keywords:

Industrial functional safety IoT QoS metrics Safety Integrity Level Wireless Sensor Networks

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Area of Science:

Industrial IoT and Industry 4.0
Functional Safety Engineering
Wireless Sensor Networks (WSN)

Background:

WSN are critical for Industry 4.0, enabling real-time data collection and machine-to-machine communication.
Safety-critical applications demand WSN compliance with Quality of Service (QoS) metrics and Safety Integrity Levels (SIL).
Existing assessments often focus on single QoS metrics, neglecting the multi-metric reality of industrial WSN.

Purpose of the Study:

To address the gap in safety assessment for industrial WSN by incorporating multiple QoS metrics.
To illustrate a practical approach for evaluating WSN safety compliance using diverse performance indicators.
To provide functional safety engineers with a method for real-time safety assessment of WSN.

Main Methods:

Leveraging random data simulation to generate key QoS metrics like delay bound (DB) and false positive detection rate (FPDR).
Employing statistical techniques for consolidating results and making decisions on SIL compliance.
Assessing WSN compliance against IEC 61508 SIL targets using multiple QoS metrics and p-value statistics.

Main Results:

Demonstrated a method for safety assessment of industrial WSN that considers multiple QoS metrics simultaneously.
Validated the significance of variations across applicable QoS metrics for safety compliance.
Provided a framework for identifying non-compliance and suggesting improvements in data communication defenses.

Conclusions:

The proposed approach enables a more comprehensive safety integrity assessment of industrial WSN.
Future research can explore advanced techniques for safety integrity assessment using QoS metrics in WSN.
This work supports the functional safety design of industrial WSN by offering a multi-metric evaluation methodology.