dc.contributor.author |
Piyaratne, M. A. M. D |
|
dc.date.accessioned |
2022-03-08T04:52:27Z |
|
dc.date.available |
2022-03-08T04:52:27Z |
|
dc.date.issued |
2021 |
|
dc.identifier.citation |
Piyaratne, M. A. M. D (2021) Improving Safety for Infant’s Sleep from SIDS using Image Recognition. BSc. Dissertation Informatics Institute of Technology |
en_US |
dc.identifier.issn |
2015053 |
|
dc.identifier.uri |
http://dlib.iit.ac.lk/xmlui/handle/123456789/864 |
|
dc.description.abstract |
"
In a world where productivity is key and an economy where inflation is rising at a staggering
rate, household find it harder and harder to meet basic needs, let alone be able to hire afford
childcare while they work.
Moreover, with the recent transformation in our culture with the Coronavirus Pandemic.
Parents are now working from home. This means they must stay productive and keep a constant
eye on their children. If they are to get any work done this work environment is not helpful.
Even when the children are asleep, they can be in danger of suffocation caused by various risk
factors discussed further down.
This research monitors infant’s care and level of risk at moments when it is least being observed
by caregivers. The system will observe the objects and the infant’s surrounding to ensure a safe
and risk-free sleep environment. The system will observe the behaviour at night to ensure that
the infant sleep in the most optimum placement/position.
" |
en_US |
dc.language.iso |
en |
en_US |
dc.subject |
Parenting |
en_US |
dc.subject |
Sudden Infant Death Syndrome |
en_US |
dc.subject |
Sudden Infant Death Early Child Development |
en_US |
dc.subject |
Deep Learning |
en_US |
dc.subject |
Neural Networks |
en_US |
dc.subject |
Machine Learning |
en_US |
dc.subject |
Classification Model |
en_US |
dc.subject |
Syndrome |
en_US |
dc.title |
Improving Safety for Infant’s Sleep from SIDS using Image Recognition |
en_US |
dc.type |
Thesis |
en_US |