Abstract

An increase in the number of working parents has led to a higher demand for remotely monitoring activities of babies through baby monitors. The baby monitors vary from simple audio and video monitoring frameworks to advance applications where we can integrate sensors for tracking vital signs such as heart rate, respiratory rate monitoring. The Internet of Things (IoT) is a network of devices where each device can is recognizable in the network. The IoT node is a sensor or device, which primarily functions as a data acquisition unit. The data acquired through the IoT nodes are wirelessly transmitted to the cloud to perform data analytics, thus assisting in remote monitoring. The deployment of IoT in applications such as smart healthcare, smart home, smart cities, smart transportation, and smart agriculture has made this a billion-dollar industry.

Affective computing, also known as emotional artificial intelligence, helps in developing systems that recognize, interpret, process, and simulate human affects. It is an interdisciplinary field of computer science, psychology, and cognitive science. The proposed system will be called Amb-I (Short for Intelligent Ambient Monitoring) deploys affective computing in baby monitoring through the Internet of Things. The proposed system recognizes the mood of the baby through the camera and records the corresponding ambient values through the ambient sensor array, which consists of a humidity sensor and temperature sensor. When the mood of the baby changes i.e. if the baby cries or feels annoyed, with help of the Amb-I sensing unit, the ambient values are checked, and the thermostat is controlled wirelessly, to maintain a desired ambiance for the baby. And if the baby continues to feel annoyed, the parents are notified immediately. The learning model for recognizing the mood of the baby is based on deep learning deployed through MATLAB on local PC or python libraries on Linux based small device environments. The controller for the Amb-I system is built based on the general-purpose computer, Raspberry-Pi 3. This cost-effective, IoT-based affective ambient monitoring system helps in maintaining an ideal ambiance for babies and improves the quality of life for both parents and babies.

Date of publication

Spring 5-14-2020

Document Type

Thesis

Language

english

Persistent identifier

http://hdl.handle.net/10950/2588

Committee members

Dr. Prabha Sundaravadivel, Ph.D. (Thesis Chair), Dr. Premananda Indic, Ph.D., Dr. Mukul V. Shirvaikar, Ph.D., Dr. Hassan El-Kishky, Ph.D.

Degree

Masters in Electrical Engineering

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