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Tech Projects
Today there is a serious problem that many elderly people are unable to obtain immediate help when experiencing a fall. My grandmother in India has had several falls over the past 5 years leading to a surgery at 91. This has resulted in severe disruption in our family lives. This motivated me to engage in a remote research internship in collaboration with Jayeeta Chowdhury, Program Director at India Health Fund, a Tata Trusts Initiative. My public health literature review was on - Using Technology to Address Falls And Risk Factors Impacting The Elderly In India .
I hypothesized that through a combination of heart rate and accelerometer sensors, a mobile application, and Wi-Fi technology, I could create a prototype of a wearable device that could autonomously determine a fall and send immediate alerts to caretakers. I decided to build a proof of concept and prototype based on such principles.
To build this project, I used Arduino micro-controller and Wi-Fi module. The Arduino will use the values from the connected heart rate sensor and accelerometer to send text or Push Notifications to the desired contacts if a fall was detected. To set up the device, the caretaker would need to use the application to enter contact information and emergency contacts if a fall occurs. The elderly person would then wear the lightweight device throughout the day. If they ever need immediate help, they can also press the button located on the wearable to contact the caretaker (or other emergency contacts) .
I am currently implementing a new feature related to contact tracing. During the COVID 19 pandemic, senior centers have been the hotspot for multiple outbreaks. The elderly population is at greater risk of serious illness from this disease and it’s even worse for them if they have conditions like asthma and heart disease. I will be using the stored historical sensor data to track other contacts who may have been within the vicinity of the patient. The application is being built using HTML/CSS/Javascript and Python based APIs to store and retrieve the sensor data.
I was fortunate to be able to present my device at IoT London. In the future, I plan to use more and improved sensors to create an accurate and precise wearable. Using the historical sensor data and it's patterns, I plan to build analytics and pro-active fault predictions.
The proof of concept is depicted below through a graphic schema:
DisposeIt by Anya, Isabella, Saachi
A significant issue in the United States is the lack of knowledge on disposing of their trash. Six pounds of trash per a day is produced by Americans but over 75% is disposed incorrectly. This waste ends up polluting the ocean and contaminating the environment. A solution my team came up with was to create an app that shows how an item should be disposed of. To create this app, I used several features like image classification, a search tool, and a database through MIT App Inventor. When the object is identified by the library, it will parse through the database (Google Spreadsheet) and return the object’s type of waste. We also provided a search tool for our users if they wanted to search for the item. Additionally, our app provides the location for places you can dispose of the object nearby. Right now we only have locations near Dublin. In the future, we will combine aspects from IRecycle and Recycle Coach, by including a GPS system for users to locate the nearest recycling facilities for certain items. This feature makes it clear for people to know exactly where to throw away their items instead of the app, solely saying that the item needs to be recycled. To use the app, users can choose between a camera button or a search button. If they press the search button, they can type the item that they want to dispose of. If they press the camera button, they can then use their camera to hover over an item and press “Classify”. The app will then give information on where the trash belongs: “Compost”, “Trash”, “Recycle”, or “Dispose in a Different Location”. If the trash should be “Disposed in a Different Location”, the app will then give information on the nearest recycling locations. There is also a feature in the app, where you can view previous objects you have searched up or classified by the camera to improve the efficiency. This app definitely has the potential to guide people who want to take care of the environment. Many people care about the environment, but they are simply uneducated on where to discard their items. DisposeIt solves this issue by helping people become more informed about their waste! DisposeIt is not only helpful, but efficient and fast when it comes to informing users about their trash disposal due to the instant image classification features we added!