ModelOps for enhanced decision-making and governance in emergency control rooms

Kay Lefevre (), Chetan Arora (), Kevin Lee (), Arkady Zaslavsky (), Mohamed Reda Bouadjenek (), Ali Hassani () and Imran Razzak ()
Additional contact information
Kay Lefevre: Deakin University
Chetan Arora: Deakin University
Kevin Lee: Deakin University
Arkady Zaslavsky: Deakin University
Mohamed Reda Bouadjenek: Deakin University
Ali Hassani: Deakin University
Imran Razzak: Deakin University

Environment Systems and Decisions, 2022, vol. 42, issue 3, 402-416

Abstract: Abstract For mission critical (MC) applications such as bushfire emergency management systems (EMS), understanding the current situation as a disaster unfolds is critical to saving lives, infrastructure and the environment. Incident control-room operators manage complex information and systems, especially with the emergence of Big Data. They are increasingly making decisions supported by artificial intelligence (AI) and machine learning (ML) tools for data analysis, prediction and decision-making. As the volume, speed and complexity of information increases due to more frequent fire events, greater availability of myriad IoT sensors, smart devices, satellite data and burgeoning use of social media, the advances in AI and ML that help to manage Big Data and support decision-making are increasingly perceived as “Black Box”. This paper aims to scope the requirements for bushfire EMS to improve Big Data management and governance of AI/ML. An analysis of ModelOps technology, used increasingly in the commercial sector, is undertaken to determine what components might be fit-for-purpose. The result is a novel set of ModelOps features, EMS requirements and an EMS-ModelOps framework that resolves more than 75% of issues whilst being sufficiently generic to apply to other types of mission-critical applications.

Keywords: ModelOps; MLOps; Emergency management; Data governance; Requirements engineering (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://link.springer.com/10.1007/s10669-022-09855-1 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:envsyd:v:42:y:2022:i:3:d:10.1007_s10669-022-09855-1

Ordering information: This journal article can be ordered from
https://www.springer.com/journal/10669

DOI: 10.1007/s10669-022-09855-1

Access Statistics for this article

More articles in Environment Systems and Decisions from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().