In the words of Adam Greenfield, the age of ubiquitous computing is here: a computing without computers, where information processing has diffused into everyday life, and virtually disappeared from view . Conventional hardware and software has evolved into everyware sensor-enabled electronic devices, virtually invisible and wirelessly connected on which we increasingly often rely for everyday activities and access to services such as banking and healthcare. The key component of everyware is embedded software, continuously interacting with its environment by means of sensors and actuators. Ubiquitous computing must deal with the challenges posed by the complex scenario of communities of everyware , in presence of environmental uncertainty and resource limitations, while at the same time aiming to meet high-level expectations of autonomous operation, predictability and robustness. This calls for the use of quantitative measures, stochastic modelling, discrete and continuous dynamics and goal-driven approaches, which the emerging quantitative software verification is unable to address at present. The central premise of the proposal is that there is a need for a paradigm shift in verification to enable everyware verification, which can be achieved through a model-based approach that admits discrete and continuous dynamics, the replacement of offline methods with online techniques such as machine learning, and the use of game-theoretic and planning techniques. The project will significantly advance quantitative probabilistic verification in new and previously unexplored directions. I will lead a team of researchers investigating the fundamental principles of everyware verification, development of algorithms and prototype implementations, and experimenting with case studies. I will also provide continued scientific leadership in the area of ubiquitous computing.