Automated House of Resilience with AI-based Measures


  • Aloïs Goeury IMT Mines Albi
  • Elizabeth Chang Griffith University, Gold Coast, Queensland, Australia


This paper presents the automated analysis of resilience capability and situation awareness of the capability readiness at one glance through the House of Resilience. We extend the concept of House of Quality into House of Resilience. The resilience attributes and measures were inspired by the work of Jnitova et al. (2022). However, such analysis is complex, usually manual and would take 3 weeks to 6 months to generate, and the interpretation of the result is another level of challenges for both junior or senior officers or employees or executives. because Resilience is an open-end concept, can be interpreted in many ways and resulting in different measures and leading to different understanding. To have a system that can unify the concept,
allow common and shared understanding of resilient capability and how it can be measured is the motivation of this study. There is no such tool available in the world. We research into open-source technology aimed at help represent the complex concept of Resilience in a simple and straight way, and we believe such system and approach will be very useful for any organization for resilience capability measure, whether it is related to workforce performance or professionalisation training systems and operation processes. This automated analysis and results visualisation represented by the House of Resilience allow quick understanding of strength and weakness of the capability readiness in near real tine or within few minutes of data collection.

Keywords: House of Resilience, Automation, Resilience Attributes, AI based Measures

Cite As

A. Goeury, E. Chang, "Automated House of Resilience with AI-based Measures",
Engineering Intelligent Systems, vol. 32 no. 1, pp. 63-75, 2024.