Context Aware Computing for The Internet of Things: A Survey

As we are moving towards the Internet of Things (IoT), the number of sensors deployed around the world is growing at a rapid pace. Market research has shown a significant growth of sensor deployments over the past decade and has predicted a significant increment of the growth rate in the future. These sensors continuously generate enormous amounts of data. However, in order to add value to raw sensor data we need to understand it. Collection, modelling, reasoning, and distribution of context in relation to sensor data plays critical role in this challenge. Context-aware computing has proven to be successful in understanding sensor data. In this paper, we survey context awareness from an IoT perspective. We present the necessary background by introducing the IoT paradigm and context-aware fundamentals at the beginning. Then we provide an in-depth analysis of context life cycle. We evaluate a subset of projects (50) which represent the majority of research and commercial solutions proposed in the field of context-aware computing conducted over the last decade (2001-2011) based on our own taxonomy. Finally, based on our evaluation, we highlight the lessons to be learnt from the past and some possible directions for future research. The survey addresses a broad range of techniques, methods, models, functionalities, systems, applications, and middleware solutions related to context awareness and IoT. Our goal is not only to analyse, compare and consolidate past research work but also to appreciate their findings and discuss their applicability towards the IoT.Comment: IEEE Communications Surveys & Tutorials Journal, 201

10. Interuniversitäres Doktorandenseminar Wirtschaftsinformatik Juli 2009

Begonnen im Jahr 2000, ist das Interuniversitäre Wirtschaftsinformatik-Doktorandenseminar mittlerweile zu einer schönen Tradition geworden. Zunächst unter Beteiligung der Universitäten Leipzig und Halle-Wittenberg gestartet. Seit 2003 wird das Seminar zusammen mit der Jenaer Universität durchgeführt, in diesem Jahr sind erstmals auch die Technische Universität Dresden und die TU Bergakademie Freiberg dabei. Ziel der Interuniversitären Doktorandenseminare ist der über die eigenen Institutsgrenzen hinausgehende Gedankenaustausch zu aktuellen, in Promotionsprojekten behandelten Forschungsthemen. Indem der Schwerpunkt der Vorträge auch auf das Forschungsdesign gelegt wird, bietet sich allen Doktoranden die Möglichkeit, bereits in einer frühen Phase ihrer Arbeit wichtige Hinweise und Anregungen aus einem breiten Hörerspektrum zu bekommen. In den vorliegenden Research Papers sind elf Beiträge zum diesjährigen Doktorandenseminar in Jena enthalten. Sie stecken ein weites Feld ab - vom Data Mining und Wissensmanagement über die Unterstützung von Prozessen in Unternehmen bis hin zur RFID-Technologie. Die Wirtschaftsinformatik als typische Bindestrich-Informatik hat den Ruf einer thematischen Breite. Die Dissertationsprojekte aus fünf Universitäten belegen dies eindrucksvoll.

Conspiracy in the Time of Corona: Automatic detection of Emerging Covid-19 Conspiracy Theories in Social Media and the News

Abstract Rumors and conspiracy theories thrive in environments of low confi- dence and low trust. Consequently, it is not surprising that ones related to the Covid-19 pandemic are proliferating given the lack of scientific consensus on the virus’s spread and containment, or on the long term social and economic ramifications of the pandemic. Among the stories currently circulating are ones suggesting that the 5G telecommunication network activates the virus, that the pandemic is a hoax perpetrated by a global cabal, that the virus is a bio-weapon released deliberately by the Chinese, or that Bill Gates is using it as cover to launch a broad vaccination program to facilitate a global surveillance regime. While some may be quick to dismiss these stories as having little impact on real-world behavior, recent events including the destruction of cell phone towers, racially fueled attacks against Asian Americans, demonstrations espousing resistance to public health orders, and wide-scale defiance of scientifically sound public mandates such as those to wear masks and practice social distancing, countermand such conclusions. Inspired by narrative theory, we crawl social media sites and news reports and, through the application of automated machine-learning methods, discover the underlying narrative frame- works supporting the generation of rumors and conspiracy theories. We show how the various narrative frameworks fueling these stories rely on the alignment of otherwise disparate domains of knowledge, and consider how they attach to the broader reporting on the pandemic. These alignments and attachments, which can be monitored in near real-time, may be useful for identifying areas in the news that are particularly vulnerable to reinterpretation by conspiracy theorists. Understanding the dynamics of storytelling on social media and the narrative frameworks that provide the generative basis for these stories may also be helpful for devising methods to disrupt their spread