HM-Req: A Framework for Embedding Values within CPS Human Monitoring Requirements

2026-05-12

AI Summary

This study addresses ethical and privacy concerns in cyber-physical systems arising from human monitoring requirements that often overlook stakeholder values, compounded by the inherent ambiguity and conflicts in natural language specifications. To tackle these challenges, this work proposes HM-Req, a novel framework that explicitly integrates human values into monitoring requirements engineering. HM-Req employs controlled natural language (CNL) to formalize requirement expressions and introduces a “value dashboard” to visualize and facilitate negotiation of value conflicts. By synergistically combining value modeling, requirements engineering, and human-computer interaction analysis, the framework demonstrates strong capability in capturing diverse monitoring needs. Empirical validation through expert evaluation and user studies confirms its practicality and clarity in expressing nuanced, value-sensitive requirements.

Abstract

Monitoring humans, for example, their movement or location, is essential for safe and efficient human-machine collaboration in Cyber-Physical Systems (CPS). This information allows CPS to ensure safety properties, adapt their behaviour dynamically, and coordinate with humans. To ensure that the design of a CPS respects ethical principles and the privacy of its stakeholders, system requirements, particularly those related to human monitoring, must reflect the human values of all involved stakeholders. However, human values are often underrepresented in Software Engineering -- particularly during requirements elicitation and system design, crucial phases when introducing ethically critical functionality. Stakeholder values are often implicit and conflicting, yet rarely systematically captured. Furthermore, unstructured natural language requirements introduce ambiguity and vagueness, complicating conflict resolution. To address these problems, we propose HM-Req, a novel requirements elicitation framework including a Controlled Natural Language (CNL) for defining human monitoring requirements. These requirements are then augmented with human values from relevant stakeholders and integrated into a Value Dashboard to detect potential conflicts that require further discussion and resolution. Validation results, applying the CNL to different datasets and conducting a survey and expert interview, confirms the CNL's ability to capture diverse human monitoring requirements and show HM-Req's usefulness for requirements elicitation activities.

Problem

• Human Values
• Requirements Elicitation
• Cyber-Physical Systems
• Ethical Design
• Stakeholder Conflicts

Innovation

• Human Values
• Controlled Natural Language
• Requirements Elicitation
• Cyber-Physical Systems
• Value Dashboard