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SmartUni 2014 - Second International Workshop SMART UNIVERSITY 2014

Date2014-11-14

Deadline2014-09-22

VenueLondon, UK - United Kingdom UK - United Kingdom

Keywords

Websitehttps://smartuni2014.workshop.hm

Topics/Call fo Papers

Sharing data and information and providing transparency are a basis for innovation and academic growth. Linking personal experience to group and university-wide experience helps develop an evidence-based view on the organisation. This new view helps revealing strengths and weaknesses of the organisation. Sensors can, for example, easily track temperature, humidity, and noise level in and outside the classroom; they can also help automatically determine actual class size. In addition, mobile sensing solutions can enhance social contexts and enable social media, especially offline interactions mediated by mobile phones or specialised sensors.
By adopting Linked Data for the university as a platform, links can be set between internal organisational and sensor data and such external data sources as weather news or traffic feeds, thereby connecting these sources into a single information space. The use of a common data model enables the use of generic applications that operate on that information space. Additionally the common data model presents opportunities for deriving new insights from that information space.
In this second workshop of the series we want to further explore the possibilities of acquiring and using contextual data. By letting students and teachers tell their story with automatically generated environmental and social data underpinning their story, the university as a platform can help prospective students and lecturers make an informed decision about their participation in the respective environment. For example, collecting sensor data on noise levels and temperature can help backing up quality complaints about co-located noisy classes or uncomfortable room temperatures.
Low-cost motion detection and other sensors coupled with low-cost credit-card sized computers such as the Raspberry Pi open up opportunities to equip rooms with sensors. As the Raspberry Pi is a full-fledged computing device running one cannot only acquire data, but also process it in context. Additionally the sensor-hubs can form radio frequency based mesh networks allowing for an infrastructure independent communication of the acquired and pre-processed sensor data. Smartphones with their sensors and processing power could collect and provide additional information and context.
Several types of contributions are of interest to this workshop, related to such areas as Context-aware Computing, Ambient Intelligence, Data Mining, Technology-enhanced Teaching and Learning, Linked Data, Pedagogy, Psychology, Explanation, Software Architectures, Embedded sensors.

Last modified: 2014-09-12 23:02:05