Monitoring of Library Collections with the Help of Raspberry Pis
Marcel Großmann (Kommunikationsdienste, Telekommunikationssysteme und Rechnernetze),
Steffen Illig (Universitätsbibliothek)
Andreas Eiermann (both institutions)
An ever-increasing amount of devices - not only computers, but
also phones, watches, sensors, actuators and various other devices
- connected over the Internet pave the road towards the
realization of the `Internet of Things' (IoT) idea. With IoT,
endangered infrastructures can easily be enriched with low-cost,
energy-efficient monitoring solutions, thus alerting is possible
before severe damage occurs. We developed a library wide humidity
and temperature monitoring framework MonTreAL, which runs on
commodity single board computers. In addition, our primary
objectives are to enable flexible data collection among a
computing cluster by migrating virtualization approaches of data
centers to IoT infrastructures. As a side benefit, we profit from
the scalability, reliability and maintainability of data center
technologies, especially container virtualization that is
available for a lot of IoT devices.
We evaluate our prototype of the system MonTreAL at the
University Library of Bamberg by collecting temperature and
humidity data.
May 30, 2017:
Predictive analytics in energy retail - Lifting the value of customer data for marketing and energy efficiency
Konstantin Hopf
May 16, 2017:
Ontology-based Data Quality Management for Data Streams
Sandra Geisler (RWTH Aachen; guest of the MOBI-group)
While today the broad availability of data streams enables new
applications, sensors and other sources producing data streams require
data quality (DQ) assessment as they are failure- and error-prone. Data
Stream Management Systems (DSMS) enable processing of data streams, but
many systems lack the ability to measure DQ in an efficient and
customizable way. In this talk an ontology-based data quality framework
for relational DSMS is presented which includes DQ measurement and
monitoring in a transparent, modular, and flexible way. The framework is
designed along a DQ management methodology suited for data streams. It
follows a three-fold approach that takes the characteristics of
relational data stream management for DQ metrics into account. The
approach has been evaluated in the domains of road traffic applications
and health monitoring. Two examples from those domains will be presented
along a methodology for designing DQ-oriented data stream applications.
May 2, 2017:
Welcome Pepper, the new Robot of the WIAI!
Sebastian Seufert and Pepper
The robot-zoo at the University of Bamberg got larger. We will introduce our newest robot member, Pepper, that can be used for research and teaching by every group of the WIAI. So if you are interested in what you can or cannot do with Pepper or whether Pepper can introduce itself, join the talk.
