<div><h3 class="t-margin-top-20"> AI-augmented framework to automate the continuous development of cyber-physical systems</h3><p class="c-project-description__text" data-se="project_description"> Artificial intelligence (AI) technologies and AI-augmented automation support can be used to improve the continuous development of cyber-physical systems (CPSs). However, despite considerable interest in AI technology, few resources are being allocated for their improvement. Thus, the EU-funded AIDOaRt project aims to efficiently support requirements, monitoring, modelling, coding, and testing activities during the CPS development process. The project proposes the use of model-driven engineering (MDE) principles and techniques to provide a model-based framework offering proper methods and related tooling. The global AIDOaRT infrastructure will work with existing data sources, including traditional IT monitoring, log events, applications and more.</p><h2>Objective</h2><p class="c-article__text">                                The project idea is focusing on AI-augmented automation supporting modeling, coding, testing, and monitoring as part of a continuous development in Cyber-Physical Systems (CPSs). The growing complexity of CPS poses several challenges throughout all software development and analysis phases, but also during their usage and maintenance.<br/><br/>Many leading companies have started envisaging the automation of tomorrow to be brought about by Artificial Intelligence (AI) tech. While the number of companies that invest significant resources in software development is constantly increasing, the use of AI in the development and design techniques is still immature.  <br/><br/>The project targets the development of a model-based framework to support teams during the automated continuous development of CPSs by means of integrated AI-augmented solutions. The overall AIDOaRT infrastructure will work with existing data sources, including traditional IT monitoring, log events, along with software models and measurements. The infrastructure is intended to operate within the DevOps process combining software development and information technology (IT) operations. Moreover, AI technological innovations have to ensure that systems are designed responsibly and contribute to our trust in their behaviour (i.e. requiring both accountability and explainability).<br/><br/>AIDOaRT aims to impact organizations where continuous deployment and operations management are standard operating procedures. DevOps teams may use the AIDOaRT framework to analyze event streams in real-time and historical data, extract meaningful insights from events for continuous improvement, drive faster deployments and better collaboration, and reduce downtime with proactive detection.                            </p></div>

Ai-augmented automation for efficient devops, a model-based framework for continuous development at runtime in cyber-physical systems

AI-augmented framework to automate the continuous development of cyber-physical systems Artificial intelligence AI technologies and AI-augmented automation support can be used to improve the continuous development of cyber-physical systems CPSs. However, despite considerable interest in AI technology, few resources are being allocated for their improvement. Thus, the EU-funded AIDOaRt project aims to efficiently support requirements, monitoring, modelling, coding, and testing activities during the CPS development process. The project proposes the use of model-driven engineering MDE principles and techniques to provide a model-based framework offering proper methods and related tooling. The global AIDOaRT infrastructure will work with existing data sources, including traditional IT monitoring, log events, applications and more.Objective The project idea is focusing on AI-augmented automation supporting modeling, coding, testing, and monitoring as part of a continuous development in Cyber-Physical Systems CPSs. The growing complexity of CPS poses several challenges throughout all software development and analysis phases, but also during their usage and maintenance.Many leading companies have started envisaging the automation of tomorrow to be brought about by Artificial Intelligence AI tech. While the number of companies that invest significant resources in software development is constantly increasing, the use of AI in the development and design techniques is still immature. The project targets the development of a model-based framework to support teams during the automated continuous development of CPSs by means of integrated AI-augmented solutions. The overall AIDOaRT infrastructure will work with existing data sources, including traditional IT monitoring, log events, along with software models and measurements. The infrastructure is intended to operate within the DevOps process combining software development and information technology IT operations. Moreover, AI technological innovations have to ensure that systems are designed responsibly and contribute to our trust in their behaviour i.e. requiring both accountability and explainability.AIDOaRT aims to impact organizations where continuous deployment and operations management are standard operating procedures. DevOps teams may use the AIDOaRT framework to analyze event streams in real-time and historical data, extract meaningful insights from events for continuous improvement, drive faster deployments and better collaboration, and reduce downtime with proactive detection.

a, r, t, i, f, i, c, i, a, l,  , i, n, t, e, l, l, i, g, e, n, c, e,  , a, u, t, o, m, a, t, i, o, n,  , s, o, f, t, w, a, r, e,  , d, e, v, e, l, o, p, m, e, n, t

EU Calls: Credit © European Union, 1998-2024 under <a href="http://creativecommons.org/licenses/by/4.0/">CC BY 4.0 licence</a>