Enabling Machine Understandable Exchange of Energy Consumption Information in Intelligent Domotic Environments

In the 21st century, all the major countries around the world are coming together to reduce the impact of energy generation and consumption on the global environment. Energy conservation and its efficient usage has become a top agenda on the desks of many governments. In the last decade, the drive to make homes automated and to deliver a better assisted living picked pace and the research into home automation systems accelerated, usually based on a centralized residential gateway. However most devised solutions fail to provide users with information about power consumption of different house appliances. The ability to collect power consumption information can lead us to have a more energy efficient society. The goal addressed in this paper is to enable residential gateways to provide the energy consumption information, in a machine understandable format, to support third party applications and services. To reach this goal, we propose a Semantic Energy Information Publishing Framework. The proposed framework publishes, for different appliances in the house, their power consumption information and other properties, in a machine understandable format. Appliance properties are exposed according to the existing semantic modeling supported by residential gateways, while instantaneous power consumption is modeled through a new modular Energy Profile ontolog

Modelling of priority pollutants releases from urban areas

In the framework of the EU project ScorePP (Source Control Options for Reducing Emissions of Priority Pollutants), dynamic PPs (priority pollutants) fate models are being developed to assess appropriate strategies for limiting the release of PPs from urban sources and for treating PPs on a variety of spatial scales. Different possible sources of PP releases were mapped and both their release pattern and their loads were quantified as detailed as possible. This paper focuses on the link between the gathered PP sources data and the dynamic models of the urban environment. This link consists of: (1) a method for the quantitative and structured storage of temporal emission pattern information, (2) the coupling of GIS-based spatial emission source data with temporal emission pattern information and (3) the generation of PP release time series to feed the dynamic sewer catchment model. Steps 2 and 3 were included as the main features of a dedicated software tool. Finally, this paper also illustrates the method’s applicability to generate model input timeseries for generic pollutants (N, P and COD/BOD) in addition to priority pollutants

BDAQ53, a versatile pixel detector readout and test system for the ATLAS and CMS HL-LHC upgrades

BDAQ53 is a readout system and verification framework for hybrid pixel detector readout chips of the RD53 family. These chips are designed for the upgrade of the inner tracking detectors of the ATLAS and CMS experiments. BDAQ53 is used in applications where versatility and rapid customization are required, such as in laboratory testing environments, test beam campaigns, and permanent setups for quality control measurements. It consists of custom and commercial hardware, a Python-based software framework, and FPGA firmware. BDAQ53 is developed as open source software with both software and firmware being hosted in a public repository.Comment: 6 pages, 6 figure