Cloud computing is revolutionizing IT environments in most fields of economy. Its service-based approach enables collaboration and data exchange on higher level, with better efficiency and parallel decreasing costs. Also manufacturing environments can benefit from cloud technology and better fulfill fast changes in market demands, by applying diverse cloud deployment models and by virtualizing manufacturing processes and assets into services. As cloud becomes the basis of most innovative manufacturing IT systems, its future role in Cyber-physical Production Systems has to be properly investigated, as their interoperability will play a role of vital importance. In this paper, after a brief introduction to cloud criticality and cloud-based manufacturing, the mutual conceptual similarities in modelling distributed industrial services of two of the major standardization frameworks for industrial Internet architectures are presented: the Industrial Internet Reference Architecture (IIRA) and the Reference Architectural Model Industrie (RAMI 4.0). It is also introduced how their integration feasibility finds a strong affinity in specifications of the Open Connectivity Unified Architecture, a service-oriented architecture candidate to the standardization of Industrial Internet of Things based manufacturing platforms. Finally, the preliminary architecture of a prototype Smart Factory is presented as a case study.

Home Care services are notoriously difficult to deliver efficiently, due to the heterogeneity of the involved actors and the usual co-morbidity of the patients assisted at home. The K4Care platform proposes an agent-based threelayered architecture aimed at addressing these two issues and facilitate the provision of these services. The development of the platform was supported by a methodology to help the automation of the modelling and implementation of the multi-agent system. The intelligent agents of the platform, which personify the Home Care domain actors, have the capability to guide the execution of administrative and medical processes, driving the flux of knowledge and control among all the involved professionals, simplifying their interactions and capturing new medical knowledge emerging from physicians. The platform also provides tools that allow medical practitioners to develop personalised treatments, adapted to the clinical and social circumstances of each patient and based on the standard international recommendations for the most frequent Home Care pathologies. The paper describes the architecture of the system, how personalised treatments are created, and how they are executed through the co-ordinated work of agents. A comparison with other relevant guideline execution systems and an evaluation of the actual state of the work are also provided.

Abstract-As urbanization proceeds at an astonishing rate, cities have to continuously improve their solutions that affect the safety, health and overall wellbeing of their residents. Smart city projects worldwide build on advanced sensor, information and communication technologies to help dealing with issues like air pollution, waste management, traffic optimization, and energy efficiency. The paper reports about the prototype of a smart city initiative in Budapest which applies various sensors installed on the public lighting system and a cloud-based analytical module.While the installed wireless multi-sensor network gathers information about a number of stressors, the module integrates and statistically processes the data. The module can handle inconsistent, missing and noisy data and can extrapolate the measurements in time and space, namely, it can create short-term forecasts and smoothed maps, both accompanied by reliability estimates. The resulting database uses geometric representations and can serve as an information centre for public services.

The paper investigates the application of solar energy in public lighting for realizing a street lighting sub-grid with positive yearly energy balance. The focus is given to the central controller of the system, which ensures the adaptive behavior of the overall system and provides smart city services to the end users via its web-based user interface. A functionality of the controller of special interest is the optimization of the energy management of the system, i.e., determining when to sell and buy electricity to/from the grid, in order to minimize the cost of electricity (or to maximize profit) subject to a given, time-of-use variable energy tariff. This requires precise forecasts of the energy produced and consumed, as well as appropriate robust optimization techniques that guarantee that the system bridges potential power outages of moderate duration in island mode. The algorithms implemented in the controller are presented in detail, together with the evaluation of the operation of a physical prototype with 191 luminaries over a horizon of six months, based on the monitoring data collected by the proposed controller.