We Care4U

Share this:

India Today       Economic   Times      Times Now      NDTV         Careers360              Newsgram             Outlook            Hindustan Times             Jagran Josh New Delhi Times                  Express Computer                        Sentinel Assam                     Manorama            The Hindu BusinessLine

For a nation with as many as 112 million elderly people, geriatric care is fast emerging as a major worry for India. Apart from a range of health problems, the elderly face loneliness, abuse, or plain neglect. Even if willing, the caregiver at times finds it inordinately difficult to reach out to the aged at the right time.

A solution might be close at hand. An interdisciplinary team of 2nd year B.Tech students of IIT Kharagpur have built two interconnected android smartphone apps under the name ‘CARE4U’ that connects the caregiver to the elderly. One of these apps can be installed on the phone of the elderly, the other on the smartphone of the caregiver.

The neural network-based fall detection algorithm in the app installed on the phone of the elderly can detect whether the elderly has fallen down. If there is a fall, it automatically calls the caregiver and emergency services with the location of the elderly person. Even if there is no internet connection, the fall detection will work.

CARE4U also has a ‘Medicine Reminder’ feature to remind both the elderly as well as the caregiver that it is time for the former to take medicine. To make a list of the medicine, all one has to do is take a photo of the medicine. The image-to-text recognition algorithm of CARE4U automatically detects the name of the medicine and adds it to the list. The user then just needs to set the time at which the medicine has to be consumed.

The android-based CARE4U app recently won the IIT Kharagpur team, Data_X, the first runners-up position at a nationwide hackathon called ‘vesAIthon’19’ sponsered by Capgemini and LeadingIndia.AI. The 24-hour AI coding event, hosted by VESIT (Vivekanand Education Society’s Institute of Technology), proposed to make an impact on the community by building a workable AI solution for the most pressing social challenges faced by senior citizens, the differently-abled and children. The final judging was done by the end users and experts.

As to why the team chose to work on elderly, Aniruddha Chattopadhyay, a 2nd year student of the Department of Industrial and Systems Engineering said, “We strongly feel that AI should impact and improve everyone’s life. Since not much has been done using AI for old people, we decided to give it a try.” Apart from Aniruddha, the team comprised Aadi Swadipto Mondal and Kanishka Halder of Electronics and Electrical Communication Engineering and Partha Sarathi Roy from the Department of Geology and Geophysics.

CARE4U can also detect emotion. Whenever the elderly opens the app, the phone takes his picture and a mood index is calculated. This detects whether the person is sad or not and automatically updates the caregiver with the timestamp. The caregiver can check what mood the senior citizen has been through in the day and perhaps talk about it.

The app also has a cognitive Intelligent chatbot for the elderly person to engage with. Kanishka Haldar says, “We customized it to recognize the current mood of the person and, accordingly, fine tune its conversations with that of the person. For example, the chatbot can recommend a motivational quote or an old song when the person is sad.”

Aadi Swadipto Mondal of the team says, “The best thing about our app is that except for the chatbot, all other Machine Learning models run on the mobile itself, so no cloud service is needed. Even if there is no internet connection, all other features such as fall detection, emotion detection will work.”

Partha Sarathi Roy adds, “CARE4U can also do a plethora of other day-to-day life activities like make a call, send a text, book a cab and so on.” The app also has a record of medical histories, allergies’ account, an SOS button, real time location tracking and so on.

Aniruddha says, “Another feature of our app is that in case we want to upgrade the tensorflow based Neural Net model, we just have to upload a tensorflow lite model in firebase from our end whenever there is a net connection. The app will then automatically sync with firebase. No hefty updates from Google Play are needed.”

Team Data_X won INR 30,000 prize money. Around 30 teams were shortlisted for the finals on June 28-29 for the hackathon finals in Mumbai.

Graphics : Suman Sutradhar

Leave a Reply

Your email address will not be published. Required fields are marked *