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Lenka, Sushmita
- IoT based Neonatal Monitoring in the ICU
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Authors
Affiliations
1 School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, IN
1 School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, IN
Source
Research Journal of Pharmacy and Technology, Vol 12, No 6 (2019), Pagination: 2885-2888Abstract
The empowering condition for safe childbirth relies upon the care and consideration required to be given for infants by effective facilities and the accessibility of sufficient human services, hardware, and medications and essential care when required in NICU. Neonatal monitoring primarily focuses on all the possible complexity issues that baby can land up in. The vital point of this system is to detect any unusual activity of the infant in early possible ways. A proposal is made with a prototype and design of a” Neonatal monitoring system” with the help of all the required sensors which keeps track of the temperature, moisture, sound and alerts doctor and nurse with the buzzer alarm. Then those data get saved in cloud for future reference.Keywords
Cloud, IoT, Neonatal, NICU, Sensors.
References
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- Lower Back Pain Classification Using Parameter Tuning
Abstract Views :153 |
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Authors
Affiliations
1 FICO - Solution Integration - Consultant, Bangalore,, IN
2 Assistant Professor, School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, IN
1 FICO - Solution Integration - Consultant, Bangalore,, IN
2 Assistant Professor, School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, IN
Source
Research Journal of Pharmacy and Technology, Vol 15, No 4 (2022), Pagination: 1573-1578Abstract
Back pain is one of the most popular diseases which cause extreme discomfort for patients. More than 80% of the people’s day to day activities are affected due to lower back pain. The symptom sometimes gets neglected and worsens the situation, which can cause lifelong damage to vital organs. Lower back pain can be classified as normal and abnormal LBP based on the boundary values of various parameters. Extensive research has been carried out in this field and most of the classification techniques serve the purpose by classifying the data with already provided accuracy values. However, this paper provides a novel technique by adding feature parameter tuning which acts as a catalyst in increasing the accuracy and thereby identifying the effective parameters that help in the optimization.Keywords
Classification, Categorization, Lower Back Pain, Medical, Parameter tuning.References
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