AI Aging
- 0 Collaborators
Most of elderly are not happy because of dependency, disability, isolation, loneliness, distress and so on. The most important reason is the poor resource and facility causing no or minimal care for elderly. So the question is "How can the AI technology help the elderly to improve the quality of life". We are building a customized AI based model to identify the specific needs of the person. The overall goal of this project to achieve all our goals, however we will build this application strategically based on priority of features. Once we achieve the success in a high priority features we will focus in an improvisation of app and then move to a medium and low priority features. ...learn more
Project status: Under Development
Virtual Reality, Internet of Things, Artificial Intelligence
Intel Technologies
OpenVINO,
AI DevCloud / Xeon,
Intel Opt ML/DL Framework,
BigDL
Overview / Usage
Overview
65 million elderly American are affected by depression. This figure is more scary in rest of world including India, China, Japan and some European countries. Most of elderly are not happy because of dependency, disability, isolation, loneliness, distress and so on. The most important reason is poor resource and facility causing no or minimal care for elderly. We offer AI-based business analytics service. We are building a customized AI-based model for the elderly population.
Usage :
This AI based app will helps the elderly in many ways. It entertains the elderly based on his choice of songs, it can remind what and what medicine you should take, it will improve your daily exercise and eating habits, It will help you to pay your bills etc.
The overall goal of this project to achieve all our goals, however we will build this application strategically based on priority of features. Once we achieve the success in high priority feature we will focus in improvisation of app and then move to medium and low priority features.
Methodology / Approach
Dataset: Open source
Architecture : CNN + LSTM
Topology : VGG
Building Application:
Xcode
HTML,
Java,
NodeJS
Methods
Step 1: Data Collection
Step 2: Data Preprocessing
Step 3: Data Augmentation and Annotation
Step 4: Splitting dataset
Step 5: Traing and testing
Step 6: Optimization
Step 7: Building app
Step 8: Deployment
Step9: Testing
Technologies Used
Hardware:
Intel Xenon Processor 32 GB RAM; Intel DevCloud; Raspberry pi
Software:
Intel Optimized Tools,
Intel Optimized Framework/Libraries (For example Tensorflow, Neon, Pandas, OpenCV, OpenVino, BigDL, H2O etc)
Operating system - Linux or Mac;
Programming languages - Python, Scala