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Master in E-Learning per la Pubblica Amministrazione

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corso_INPS___e_learning_PA___Politecnico_Torino.jpg"E-Learning per la Pubblica Amministrazione: Metodologia e Strumenti per la Formazione On-line": è questo il titolo di un nuovo Master (Corso Universitario di Aggiornamento Professionale) di 40 ore organizzato dal Politecnico di Torino con l'accreditamento ed il finanziamento di INPS.

Le iscrizioni, gratuite e rivolte ai dipendenti delle pubbliche amministrazioni, sono aperte fino al 15/04/2014.

Le lezioni si svolgeranno parte in aula (6 incontri tra il 12/05/2014 ed il 29/09/2014) e parte on-line, attraverso una piattaforma di e-learning, con metodologia di "blended learning".

 

Last Updated on Saturday, 22 March 2014 18:27 Read more...
 

LOV DogOnt

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DogOnt, the ontology that empowers the Dog gateway, has been included in the LOV (Linked Open Vocabulary) dataset.

The LOV dataset, as described in its website, contains:

"[...] the description of RDFS vocabularies or OWL ontologies used or usable by datasets in the Linked Data Cloud. Those descriptions contain metadata either formally declared by the vocabulary publishers or added by the LOV curators."

Have a look at the details of DogOnt as reported on the LOV website: http://lov.okfn.org/dataset/lov/details/vocabulary_dogont.html

Last Updated on Monday, 14 April 2014 18:57
 

Dog 3.0 is out!

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The Domotic OSGi Gateway (Dog) is a long-lived project: the first implementation dates back to the 2006, while the first publication has been realized in the 2008. In the same year, the sourceforge project was created to distribute its source code.

Things change: the Domotic OSGi Gateway, in 2014, becomes "just" Dog!

Today, 25th of February, the third version of the Dog gateway has been released with a new logo, a dedicated website (http://dog-gateway.github.io) and a Twitter profile!

Dog, nowadays, is an open source, OSGi compliant implementation of a smart environment gateway and IoT platform featuring multi-protocol capabilities, REST-based application APIs, and much more...

The new binary and source code can be downloaded from GitHub (yes, we moved away from sourceforge).

Stay tuned for further news about Dog by reading our blog or following us on Twitter!

Last Updated on Wednesday, 26 February 2014 22:58
 

Z-Wave portable energy profiler

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AimoneDavide_cover.pngThe advancement of home automation solutions, in particular when based on wireless networks and devices, allows new scenarios to be integrated into householders lifestyle. In particular, it is now both feasible and economically sustainable to collect, monitor, analyze and visualize data and information related to energy consumption (and production) inside redidential homes. The availability of such information enables house inhabitants to better understand, and therefore adapt, their energy-related behaviors, and ultimately to be more energy-efficient and environmentally friendly.

The Master Thesis of Davide Aimone, who recently graduated in Computer Engineering, proposes an easy to use energy profiler system, built upon off-the-shelf home automation components (based on the Z-Wave standard) integrated with low-cost processing hardware (Raspberry PI and RaZberry Daughter Card) and open source software (the Dog 2.6 OSGi gateway). The overall system may be used to monitor the global consumption of the house and of some specific plugs and appliances, and the collected data may be analyzed, both on-line and off-line.

For more information about the Z-Wave portable energy profiler in the context of smart homes, please see Davide Aimones's Master Thesis materials:

 

Last Updated on Tuesday, 17 December 2013 12:31
 

Business Intelligence for Energy Managers

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Paracchino_Energy_BI.pngSmart buildings and "smart energy" applications generate huge amounts of data, that is hard to manage, understand and visualize. In particular, in the energy sector, data collected by environmental sensors and energy meters located in the building are highly variable in terms of physical quantities, units of measure, sampling frequency, and covered areas.

A business-intelligence approach is therefore needed, and ofted used, to aggregate all these data streams and to offer powerful analysis and visualization solutions. Unfortunately, such BI systems are often configured by data analysts, that not always understand the needs of energy managers.

The Master Thesis of Matteo Paracchino, who recently graduated in Management Engineering, explores the data analysis and visualization issue from the point of view of the Energy Managers: a national-wide survey has been conducted across all registered energy managers. The survey highlights the main needs and requirements of energy managers in terms of granularity of data collection, type of data analysis, and nature of the visualization solutions.

Starting from this valuable set of requirements, the thesis proceeds to building a BI solution, using open-source tools, that analyzes the data provided by the Smart and Green Building management services of Politecnico di Torino.

For more information about Business Intelligence applications for Energy Managers in the context of smart buildings, please see Matteo Paracchino's Master Thesis materials:

Last Updated on Tuesday, 17 December 2013 12:31
 
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