4,498 research outputs found
DESIGN FRAMEWORK FOR INTERNET OF THINGS BASED NEXT GENERATION VIDEO SURVEILLANCE
Modern artificial intelligence and machine learning opens up new era towards video
surveillance system. Next generation video surveillance in Internet of Things (IoT) environment is
an emerging research area because of high bandwidth, big-data generation, resource constraint
video surveillance node, high energy consumption for real time applications. In this thesis, various
opportunities and functional requirements that next generation video surveillance system should
achieve with the power of video analytics, artificial intelligence and machine learning are
discussed. This thesis also proposes a new video surveillance system architecture introducing fog
computing towards IoT based system and contributes the facilities and benefits of proposed system
which can meet the forthcoming requirements of surveillance. Different challenges and issues
faced for video surveillance in IoT environment and evaluate fog-cloud integrated architecture to
penetrate and eliminate those issues.
The focus of this thesis is to evaluate the IoT based video surveillance system. To this end,
two case studies were performed to penetrate values towards energy and bandwidth efficient video
surveillance system. In one case study, an IoT-based power efficient color frame transmission and
generation algorithm for video surveillance application is presented. The conventional way is to
transmit all R, G and B components of all frames. Using proposed technique, instead of sending
all components, first one color frame is sent followed by a series of gray-scale frames. After a
certain number of gray-scale frames, another color frame is sent followed by the same number of
gray-scale frames. This process is repeated for video surveillance system. In the decoder, color
information is formulated from the color frame and then used to colorize the gray-scale frames. In
another case study, a bandwidth efficient and low complexity frame reproduction technique that is
also applicable in IoT based video surveillance application is presented. Using the second
technique, only the pixel intensity that differs heavily comparing to previous frame’s
corresponding pixel is sent. If the pixel intensity is similar or near similar comparing to the
previous frame, the information is not transferred. With this objective, the bit stream is created for
every frame with a predefined protocol. In cloud side, the frame information can be reproduced by
implementing the reverse protocol from the bit stream.
Experimental results of the two case studies show that the IoT-based proposed approach
gives better results than traditional techniques in terms of both energy efficiency and quality of the video, and therefore, can enable sensor nodes in IoT to perform more operations with energy
constraints
Global disease monitoring and forecasting with Wikipedia
Infectious disease is a leading threat to public health, economic stability,
and other key social structures. Efforts to mitigate these impacts depend on
accurate and timely monitoring to measure the risk and progress of disease.
Traditional, biologically-focused monitoring techniques are accurate but costly
and slow; in response, new techniques based on social internet data such as
social media and search queries are emerging. These efforts are promising, but
important challenges in the areas of scientific peer review, breadth of
diseases and countries, and forecasting hamper their operational usefulness.
We examine a freely available, open data source for this use: access logs
from the online encyclopedia Wikipedia. Using linear models, language as a
proxy for location, and a systematic yet simple article selection procedure, we
tested 14 location-disease combinations and demonstrate that these data
feasibly support an approach that overcomes these challenges. Specifically, our
proof-of-concept yields models with up to 0.92, forecasting value up to
the 28 days tested, and several pairs of models similar enough to suggest that
transferring models from one location to another without re-training is
feasible.
Based on these preliminary results, we close with a research agenda designed
to overcome these challenges and produce a disease monitoring and forecasting
system that is significantly more effective, robust, and globally comprehensive
than the current state of the art.Comment: 27 pages; 4 figures; 4 tables. Version 2: Cite McIver & Brownstein
and adjust novelty claims accordingly; revise title; various revisions for
clarit
Multiagent Intelligent System of Convergent Sensor Data Processing for the Smart&Safe Road
The results of monitoring and analyzing traffic accidents, fixed by an intelligent monitoring system with photoradar complexes, are considered. The system works with a network of distributed photoradar vehicle detectors for road accidents, video surveillance cameras, vehicle information and communication systems, built-in car navigation equipment and mobile communication equipment. A multiagent approach developed to address the tasks of sensor data collecting and processing. The system functionality is implemented by several agents that perform data collecting, cleaning, clustering, comparing time series, retrieving data for visualization, preparing charts and reports, performing spatial and intellectual analysis, etc. Convergent approach is the convergence of cloud, fog and mobile data processing technologies. The diagnostic system is necessary for remote maintenance of photoradar equipment. The structure of the neural network is adapted to the diagnosing problems and forecasting. The tasks of intellectual analysis and forecasting traffic accidents are solved. The hybrid fuzzy neural network is synthesized. Because of the comparison of time series of traffic accidents and time series of meteorological factors, the presence of factors to become determinants for an abnormal change in the traffic situation in controlled areas is established
Mission-Critical Communications from LMR to 5G: a Technology Assessment approach for Smart City scenarios
Radiocommunication networks are one of the main support tools of agencies that carry out
actions in Public Protection & Disaster Relief (PPDR), and it is necessary to update these
communications technologies from narrowband to broadband and integrated to information
technologies to have an effective action before society. Understanding that this problem
includes, besides the technical aspects, issues related to the social context to which these
systems are inserted, this study aims to construct scenarios, using several sources of
information, that helps the managers of the PPDR agencies in the technological decisionmaking
process of the Digital Transformation of Mission-Critical Communication considering
Smart City scenarios, guided by the methods and approaches of Technological Assessment
(TA).As redes de radiocomunicações são uma das principais ferramentas de apoio dos órgãos que
realizam ações de Proteção Pública e Socorro em desastres, sendo necessário atualizar essas
tecnologias de comunicação de banda estreita para banda larga, e integra- las às tecnologias
de informação, para se ter uma atuação efetiva perante a sociedade . Entendendo que esse
problema inclui, além dos aspectos técnicos, questões relacionadas ao contexto social ao qual
esses sistemas estão inseridos, este estudo tem por objetivo a construção de cenários,
utilizando diversas fontes de informação que auxiliem os gestores destas agências na tomada
de decisão tecnológica que envolve a transformação digital da Comunicação de Missão Crítica
considerando cenários de Cidades Inteligentes, guiado pelos métodos e abordagens de
Avaliação Tecnológica (TA)
Audio beacon technologies, surveillance and social order
This thesis explores audio beacon technology with the aim of elucidating the implications of this technology for the individual in contemporary society. Audio beacons are hidden inside digital devices. They emit and receive high frequency audio signals which are inaudible to the human ear, thereby generating and transmitting data without our knowledge. The motivation for this research is to raise awareness of the prevalence of audio beacon technologies and to explore their implications for contemporary society. The research takes an interdisciplinary approach involving – 1) a survey of audio beacon technology, 2) a contextualization in terms of contemporary theories of surveillance and control and 3) an interpretation in terms of 20th century dystopian literature. The hidden surveillance and privacy of this technology is examined mainly through the humanistic perspective of George Orwell’s book Nineteen Eighty-Four. The general conclusion formed is that audio beacon technologies can serve as a surveillance method enhancing authoritarian and exploitative regimes. To mitigate the negative impacts of audio beacons, this research proposes two types of solutions – 1) individual actions that will have an immediate effect and 2) governmental legislation that can improve privacy in the longer term. Both of these solutions cannot happen without a raised public awareness, towards which this research hopes to make a contribution. Finally, this research introduces the notion of a \u27digital paradox\u27 in which the dystopian worlds of George Orwell and Aldous Huxley are brought together in order to characterize surveillance and control in contemporary society
Enabling Artificial Intelligence Analytics on The Edge
This thesis introduces a novel distributed model for handling in real-time, edge-based video analytics. The novelty of the model relies on decoupling and distributing the services into several decomposed functions, creating virtual function chains (V F C
model). The model considers both computational and communication constraints. Theoretical, simulation and experimental results have shown that the V F C model can enable the support of heavy-load services to an edge environment while improving the footprint of the service compared to state-of-the art frameworks. In detail, results on the V F C model have shown that it can reduce the total edge cost, compared with a monolithic and a simple frame distribution models. For experimenting on a real-case scenario, a testbed edge environment has been developed, where the aforementioned models, as well as a general distribution framework (Apache Spark ©), have been deployed. A cloud service has also been considered. Experiments have shown that V F C can outperform all alternative approaches, by reducing operational cost and improving the QoS. Finally, a migration model, a caching model and a QoS monitoring service based on Long-Term-Short-Term models are introduced
Big Data Ethics in Research
The main problems faced by scientists in working with Big Data sets, highlighting the main ethical issues, taking into account the legislation of the European Union. After a brief Introduction to Big Data, the Technology section presents specific research applications. There is an approach to the main philosophical issues in Philosophical Aspects, and Legal Aspects with specific ethical issues in the EU Regulation on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95/46/EC (Data Protection Directive - General Data Protection Regulation, "GDPR"). The Ethics Issues section details the specific aspects of Big Data. After a brief section of Big Data Research, I finalize my work with the presentation of Conclusions on research ethics in working with Big Data.
CONTENTS:
Abstract
1. Introduction
- 1.1 Definitions
- 1.2 Big Data dimensions
2. Technology
- 2.1 Applications
- - 2.1.1 In research
3. Philosophical aspects
4. Legal aspects
- 4.1 GDPR
- - Stages of processing of personal data
- - Principles of data processing
- - Privacy policy and transparency
- - Purposes of data processing
- - Design and implicit confidentiality
- - The (legal) paradox of Big Data
5. Ethical issues
- Ethics in research
- Awareness
- Consent
- Control
- Transparency
- Trust
- Ownership
- Surveillance and security
- Digital identity
- Tailored reality
- De-identification
- Digital inequality
- Privacy
6. Big Data research
Conclusions
Bibliography
DOI: 10.13140/RG.2.2.11054.4640
- …