Difference between revisions of "SmartC"

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(Created page with "{{StudentProjectTemplate |Summary=Using stock devices for unobtrusive fall detection |Programme=EIS Masters 15hpc |Keywords=Smart homes, pervasive computing, DiaSuite |TimeFra...")
 
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{{StudentProjectTemplate
 
{{StudentProjectTemplate
|Summary=Using stock devices for unobtrusive fall detection
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|Summary=Choice of one of several projects
 
|Programme=EIS Masters 15hpc
 
|Programme=EIS Masters 15hpc
|Keywords=Smart homes, pervasive computing, DiaSuite
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|Keywords=Smart Cities, Autonomous Driving
 
|TimeFrame=6 months
 
|TimeFrame=6 months
|References=Please see text
 
|Prerequisites=DA8003 Cyber-Physical Systems
 
 
|Supervisor=Walid Taha
 
|Supervisor=Walid Taha
|Examiner=Antanas Verikas
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|Examiner=Tomas Nordström
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|Author=Walid Taha
 
|Level=Master
 
|Level=Master
 
|Status=Ongoing
 
|Status=Ongoing
 
}}
 
}}
The core research question is to whether stock devices can be used to effectively detect fall events in the home.
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Smart Cities and Autonomous Driving pose numerous challenges for engineers and city planners. SmartC is a project at Halmstad University to build a model Smart Cities environment to enable students, researchers, and policy makers to understand and plan cities. For a masters thesis, a student can chose to work on any of 20+ project topics listed in the SmartC project announcement (http://bit.ly/SmartCitySummer). Students should expect to work in groups of two on their thesis, and to work also with undergraduate students or interns from other schools. Most of the work needs to be done after March 1st 2018.
This project will be aligned with ongoing work at Charles Consel's research group at INRIA Bordeaux, France.
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The research question involves primarily building a fall detection system using readily available components using the DiaSuite platform, and then evaluating it effectiveness at detecting falls.
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The first component of the work is learn how DiaSuite works and make an installation at the HH smart home environment.
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The second component is to identify a base line fall detection device that can be used for comparing the new solution.
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The third component is a state of the art review.
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The fourth is to use DiaSuite to explore multiple options for detecting falls, including smart phones, basic motion sensors, specialized motion sensors (such as the kinect), and others.
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The fifth component is the evaluation of detection methods that have been developed in the project. This involves using the models to test the tools to see if they are able to produce the expected results in a satisfactory manner.
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The sixth component is writing up the results of the work.
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References:
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https://hal.inria.fr/hal-00702909/file/diasuite.pdf
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https://www.ncbi.nlm.nih.gov/pubmed/21096573
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http://subs.emis.de/LNI/Proceedings/Proceedings208/1456.pdf
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http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=6610594
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http://link.springer.com/chapter/10.1007%2F978-3-642-40261-6_55
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Revision as of 12:55, 26 September 2018

Title SmartC
Summary Choice of one of several projects
Keywords Smart Cities, Autonomous Driving
TimeFrame 6 months
References
Prerequisites
Author Walid Taha
Supervisor Walid Taha
Level Master
Status Ongoing

Generate PDF template

Smart Cities and Autonomous Driving pose numerous challenges for engineers and city planners. SmartC is a project at Halmstad University to build a model Smart Cities environment to enable students, researchers, and policy makers to understand and plan cities. For a masters thesis, a student can chose to work on any of 20+ project topics listed in the SmartC project announcement (http://bit.ly/SmartCitySummer). Students should expect to work in groups of two on their thesis, and to work also with undergraduate students or interns from other schools. Most of the work needs to be done after March 1st 2018.