scholarly journals Implementation of Automated Baby Monitoring: CCBeBe

2020 ◽  
Vol 12 (6) ◽  
pp. 2513
Author(s):  
Soohyun Choi ◽  
Songho Yun ◽  
Byeongtae Ahn
Keyword(s):  
Facial Expression ◽  
Video Streaming ◽  
Android Application ◽  
Voice Transmission ◽  
Monitoring Service ◽  
Video Diary

An automated baby monitoring service CCBeBe (CCtv Bebe) monitors infants’ lying posture and crying based on AI and provides parents-to-baby video streaming and voice transmission. Besides, parents can get a three-minute daily video diary made by detecting the baby’s emotion such as happiness. These main features are based on OpenPose, EfficientNet, WebRTC, and Facial-Expression-Recognition.Pytorch. The service is integrated into an Android application and works on two paired smartphones, with lowered hardware dependence.

MackDroid - An Android based Application to monitor devices

2016 ◽  
Vol 9 ◽  
pp. 1
Author(s):  
Maaz Sirkhot ◽  
Ekta Sirwani ◽  
Aishwarya Kourani ◽  
Akshit Batheja ◽  
Kajal Jethanand Jewani
Keyword(s):  
Operating System ◽  
Open Source ◽  
Vital Role ◽  
Mobile Users ◽  
Android Application ◽  
Web Page ◽  
Technological World ◽  
Monitoring Service ◽  
User Friendly

In this technological world, smartphones can be considered as one of the most far-reaching inventions. It plays a vital role in connecting people socially. The number of mobile users using an Android based smartphone has increased rapidly since last few years resulting in organizations, cyber cell departments, government authorities feeling the need to monitor the activities on certain targeted devices in order to maintain proper functionality of their respective jobs. Also with the advent of smartphones, Android became one of the most popular and widely used Operating System. Its highlighting features are that it is user friendly, smartly designed, flexible, highly customizable and supports latest technologies like IoT. One of the features that makes it exclusive is that it is based on Linux and is Open Source for all the developers. This is the reason why our project Mackdroid is an Android based application that collects data from the remote device, stores it and displays on a PHP based web page. It is primarily a monitoring service that analyzes the contents and distributes it in various categories like Call Logs, Chats, Key logs, etc. Our project aims at developing an Android application that can be used to track, monitor, store and grab data from the device and store it on a server which can be accessed by the handler of the application.

Estimation of the Quality of Experience During Video Streaming From Facial Expression and Gaze Direction

2020 ◽  
Vol 17 (4) ◽  
pp. 2702-2716
Author(s):  
Simone Porcu ◽  
Alessandro Floris ◽  
Jan-Niklas Voigt-Antons ◽  
Luigi Atzori ◽  
Sebastian Moller
Keyword(s):  
Facial Expression ◽  
Video Streaming ◽  
Quality Of Experience ◽  
Gaze Direction

scholarly journals A Review on: Video Streaming using Cloud Computing Based on Android Application

2018 ◽  
Vol Volume-2 (Issue-4) ◽  
pp. 457-461
Author(s):  
Miss. Shailja S. Panhalkar ◽  
Mr. H. P. Khandagale ◽  
Keyword(s):  
Cloud Computing ◽  
Video Streaming ◽  
Android Application

scholarly journals Proof-of-Concept Study: a Mobile Application to Derive Clinical Outcome Measures from Expression and Speech for Mental Health Status Evaluation

2020 ◽  
Vol 44 (12) ◽  
Author(s):  
Francesco Luke Siena ◽  
Michael Vernon ◽  
Paul Watts ◽  
Bill Byrom ◽  
David Crundall ◽  
...  
Keyword(s):  
Health Status ◽  
Facial Expression ◽  
Outcome Measures ◽  
Mobile Application ◽  
Autism Spectrum ◽  
Mobile App ◽  
Proof Of Concept ◽  
Concept Study ◽  
Video Footage ◽  
Video Diary

AbstractThis proof-of-concept study aimed to assess the ability of a mobile application and cloud analytics software solution to extract facial expression information from participant selfie videos. This is one component of a solution aimed at extracting possible health outcome measures based on expression, voice acoustics and speech sentiment from video diary data provided by patients. Forty healthy volunteers viewed 21 validated images from the International Affective Picture System database through a mobile app which simultaneously captured video footage of their face using the selfie camera. Images were intended to be associated with the following emotional responses: anger, disgust, sadness, contempt, fear, surprise and happiness. Both valence and arousal scores estimated from the video footage associated with each image were adequate predictors of the IAPS image scores (p < 0.001 and p = 0.04 respectively). 12.2% of images were categorised as containing a positive expression response in line with the target expression; with happiness and sadness responses providing the greatest frequency of responders: 41.0% and 21.4% respectively. 71.2% of images were associated with no change in expression. This proof-of-concept study provides early encouraging findings that changes in facial expression can be detected when they exist. Combined with voice acoustical measures and speech sentiment analysis, this may lead to novel measures of health status in patients using a video diary in indications including depression, schizophrenia, autism spectrum disorder and PTSD amongst other conditions.

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