2026· Proceedings of the 21st International Conference on Software Technologies· pp. 278-284· 0 citations· 39 references
TL;DR
A pattern language for green computing is envisioned, covering the various phases of the software lifecycle in which green computing solutions can be applied, as well as important application areas, such as artificial intelligence or cloud computing.
Abstract
: Software is used in our modern world to increase automation in almost all areas: From simple calculations to complex tasks, such as self-driving vehicles or coding agents based on artificial intelligence. While this automation increases efficiency and convenience for the users, it has an often overlooked negative impact on the environment, primarily caused by the severe energy and water consumption. Various approaches to reduce this impact and to develop and operate software more sustainably were developed in recent years. However, the wide adoption of these approaches is currently missing due to a lack of knowledge about green software development, operations, and usage. Hence, a common knowledge base must be established that facilitates applying green computing solutions. Patterns are a well-known concept to document and share knowledge about proven solutions to commonly recurring problems in an abstract manner. Therefore, they are also promising for documenting green computing solutions and best practices and to use them for reference or educational purposes. However, there exists no pattern language documenting and connecting relevant knowledge about green software development, operation, and usage. In this paper, we envision a pattern language for green computing, covering the various phases of the software lifecycle in which green computing solutions can be applied, as well as important application areas, such as artificial intelligence or cloud computing.
An integrated human‑automation teaming framework is presented that facilitates TDP development and supports cross‑disciplinary dialogue between designers, engineers, command staff, and policy‑makers and provides a structured basis for designing flexible and context‑appropriate adaptive automation in VUCA environments.
Jelle A Van Dijk, Rosa van Tuijn, Renske Verwaal-Bootsma et al.· AHFE International· 0 citations
This paper aims at building an algorithm of combining ISO 15765-4 and SAE J1979 compliant professional scan tools technologies with Microsoft Copilot for evolving the automotive diagnosis process, and consists of a set of procedures and steps that should be followed, for building an intelligent agent.
Cosmin Tomozei, I. Furdu, Bogdan Pătruț· INTERNATIONAL JOURNAL OF COM...· 0 citations
This research demonstrates that when designed with ergonomics, human values, and socio‑technical principles at the center, agentic AI become powerful enablers of human‑centric, resilient, and adaptive enterprises.
Elizabeth Koumpan, Laurentiu Gabriel Ghergu, Łukasz Strack et al.· AHFE International· 0 citations
It is demonstrated that multiple architectural views, continuous monitoring, domain-driven decomposition, and AI-assisted design techniques contribute significantly to improving scalability, maintainability, adaptability, and long-term software sustainability.
The work that the UK Data Service has so far undertaken to move ODRL from a standard to an implementable set of metadata, workflows, and tools is outlined and how standards such as Data Use Ontology (DUO) and Data Privacy Vocabulary (DPV) complement ODRL within that context is described.
D. Bell, S. McEachern, D. Lungley· International Journal of Pop...· 0 citations
The authors establish the main issues associated with scalability, security, and maintainability and show future research perspectives of sustainable adoption of RPA in large-scale enterprise settings.
Kenji Sato, Aiko Yamamoto· International Journal of Mod...· 0 citations
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