IoT-Powered Baby Care: enhancing safety and convenience with a smart baby cradle featuring face orientation detection using multi-task cascaded convolutional neural networks (MTCNN) (Record no. 25675)

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fixed length control field 03315nam a2200289Ia 4500
001 - CONTROL NUMBER
control field 90440
003 - CONTROL NUMBER IDENTIFIER
control field FT7825
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20251010130154.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 240524n 000 0 eng d
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Description conventions rda
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Language code of text/sound track or separate title engtag
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Classification number T58.6 A85 2024
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Classification number .
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Asis, Jaymark Laurence D.; Barceleno, Jacob E.; Mariano, Marc Ernest C.
245 #0 - TITLE STATEMENT
Title IoT-Powered Baby Care: enhancing safety and convenience with a smart baby cradle featuring face orientation detection using multi-task cascaded convolutional neural networks (MTCNN)
264 ## - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture Manila:
Name of producer, publisher, distributor, manufacturer PLM,
Date of production, publication, distribution, manufacture, or copyright notice c2024
300 ## - PHYSICAL DESCRIPTION
Other physical details Undergraduate Thesis: (Bachelor of Science in Information Technology) - Pamantasan ng Lungsod ng Maynila, 2024.
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Media type code unmediated
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Audience term 2
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Formatted contents note ABSTRACT: This study addresses the growing need for advanced infant care solutions by proposing the design and development of an Internet of Things (IoT)-enabled smart baby cradle. Focused on enhancing infant safety and well-being, especially in relation to reducing the risk of Sudden Infant Death Syndrome (SIDS), the system incorporates Multi-task Cascaded Convulutional Neural Network (MTCNN) technology for neonate face detection and facial feature alignment. The smart cradle integrates environmental sensors, a speaker system for soothing sounds, and a motorized system for comforting movements, all controlled by a Raspberry Pi 4 Model B. Following the Waterfall Development Methodology, the research undergoes Requirements Gathering, System Design, Implementation, Integration and Testing, Deployment, and Maintenance phases. Notably, this study uses assessed the device and application using ISO 25010:2011 standards, specifically focusing on functional suitability, usability, reliability, and portability. The results indicate high satisfaction with IoT-powered smart baby cradle, with mean scores above 3.26 (out of 4) for functional suitability, usability, reliability, and portability. Notably, the cradle received favorable ratings for swaying motion (3.514), features (3.629), safety and well-being (3.429), alert systems (3.514), automatic response (3.457), and portability features (3.314). The MTCNN model demonstrated robust face detection performance across varying levels of image complexity, achieving commendable area under the curve (AUC) values of 0.801, 0.771, and 0.526 for Easy, Medium, and Hard sets, respectively. Additionally, on the FDDB benchmark, the MTCNN exhibited a True Positive rate of 0.93 and an Average Precision of 0.901, showcasing its effectiveness in accurately identifying faces. The integration of infant face detection, tracking, and a Sleep Analysis module in this research showcases the system’s effectiveness in enhancing infant safety and sleep quality while providing parents with remote monitoring capabilities. This interdisciplinary approach underscores the potential of IoT technology to address safety concerns, improve caregiving experiences, and contribute to the advancement of infant care practices, emphasizing the importance of user-centered design for tailored solutions.
526 ## - STUDY PROGRAM INFORMATION NOTE
Classification Filipiniana
540 ## - TERMS GOVERNING USE AND REPRODUCTION NOTE
Terms governing use and reproduction 5
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Genre/form data or focus term academic writing
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Institution code [OBSOLETE] lcc
Item type Thesis/Dissertation
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Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Collection code Permanent Location Current Location Shelving location Date acquired Fund Source Total Checkouts Full call number Barcode Date last seen Date last checked out Item type
          Filipiniana-Thesis PLM PLM Filipiniana Section 2024-06-06 Donation 1 T58.6 A85 2024 FT7825 2025-10-10 2025-10-09 Thesis/Dissertation

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