This book constitutes the refereed proceedings of the 15th European Conference on Ambient Intelligence, AmI 2019, held in Rome, Italy, in November 2019. The 20 full papers presented together with 10 short papers were carefully reviewed and selected from 50 submissions. The papers cover topics such as embedded devices that can merge unobtrusively and in natural ways using information and intelligence hidden in the network connecting these devices (e.g., the Internet of Things). The main topic of AmI 2019 was "Data-driven Ambient Intelligence," which follows the vision of Calm Technology, where technology is useful but does not demand our full attention or interfere with our usual behavior and activities.

Wireless sensor networks are about to be part of everyday life. Homes and workplaces capable of self-controlling and adapting air-conditioning for different temperature and humidity levels, sleepless forests ready to detect and react in case of a fire, vehicles able to avoid sudden obstacles or possibly able to self-organize routes to avoid congestion, and so on, will probably be commonplace in the very near future. Mobility plays a central role in such systems and so does passive mobility, that is, mobility of the network stemming from the environment itself. The population protocol model was an intellectual invention aiming to describe such systems in a minimalistic and analysis-friendly way. Having as a starting-point the inherent limitations but also the fundamental establishments of the population protocol model, we try in this monograph to present some realistic and practical enhancements that give birth to some new and surprisingly powerful (for these kind of systems) computational models. Table of Contents: Population Protocols / The Computational Power of Population Protocols / Enhancing the model / Mediated Population Protocols and Symmetry / Passively Mobile Machines that Use Restricted Space / Conclusions and Open Research Directions / Acronyms / Authors' Biographies