Today, embedded applications become large scale and strongly constrained. They require a decentralised embedded intelligence generating challenges for embedded systems. A multi-agent approach is well suited to model and design decentralised embedded applications. It is naturally able to take up some of these challenges. But some specific points have to be introduced, enforced or improved in multi-agent approaches to reach all features and all requirements. In this article, we present a study of specific activities that can complement multi-agent paradigm in the 'embedded' context. We use our experience with the DIAMOND method to introduce and illustrate these features and activities.Keywords: multi-agent systems; MAS; collective intelligence; embedded multi-agent systems; agent oriented analysis; agent design; collective cyber-physical systems; real world applications.Reference to this paper should be made as follows: Jamont, J-P. and Occello, M. (2015) 'Meeting the challenges of decentralised embedded applications using multi-agent systems', Int.