Human Pose Estimation
Designed to automate elbow/knee joint angle measurement using AI and real-time feedback.
• System solves this problem by using Human Pose Estimation (HPE) technology with Artificial Intelligence to measure elbow/knee angles automatically.
CrashGuard
CrashGuard is an AI-powered vehicle safety system designed to prevent accidents caused by drowsy driving.
• It uses a machine learning model trained in Pictoblox to monitor the driver’s eye movements using a webcam.
FurEver Buddy
FurEver Buddy is a project to help working professionals to take care of their fur member of family in the field of feeling of separation, aggression and sadness.
EyeGPT
An app that uses advanced image analysis to diagnose strabismus and its specific type with high accuracy.
It offers personalized solutions, including eye exercises and fun games, to improve eye coordination.
With a user-friendly interface, it empowers users to actively manage their eye health and work towards better vision. With its easy-to-use interface, the app allows users to take charge of their eye health and follow their treatment plan at their own pace. This comprehensive approach not only aids in improving vision but also helps users maintain long-term progress, boosting both their confidence and overall well-being.
Smart Sign Language Tutor
Our project aims to develop a Smart Sign Language Robotic Hand that translates text input into sign language gestures using Pictoblox, Arduino, and Servo Motors.
AI Nail Disease Detector
This multi-disease detection system will help in early diagnosis of various health conditions using just nail images, making it a non-invasive and affordable tool for remote healthcare and self-monitoring.
It analyzes dataset of nail images and predicts whether a person has diseases like Acral Lentiginous Melanoma, Pitting, Anemia, and Onychogryphosis. A non-invasive, AI-powered solution is needed to analyze nail images, detect diseases, and help users connect with nearby doctors for proper medical guidance.
Air Quality Index
Urban Air Quality Index Project
This project evaluates urban air quality (Good – Moderate – Harmful – Highly Toxic) by analyzing pollutant gases such as nitrogen dioxide (NO₂), carbon monoxide (CO), and others caused by traffic and industrial activities. It uses machine learning, specifically regression algorithms, to process gas concentration data collected by specialized sensors. To simplify the initial learning phase, ready-made datasets were used instead of direct sensor input.
SAItism Buddy App & Guide
Saitism Buddy App and Guide is an innovative project designed to support autistic children, particularly those with ADHD, in understanding their environment, people, and social behaviors. The app acts as a shadow teacher and mentor buddy, providing interactive guidance and emotional support to help them integrate better into society. It offers personalized assistance through AI-powered features, making learning and communication easier, especially for families facing financial constraints. The guide component serves as an educational resource for parents and caregivers, ensuring they can effectively support their child’s development.
Biomedical Cough Classifier
Final 200-250 word
The Biomedical Cough Classifier (BCC), “Cough once, know your risk.” By using machine learning and AI, our system can accurately identify COVID-like coughs, regular coughs, and background noise. Our idea was inspired by the ongoing challenges faced by people around the world—especially medical personnel fighting on the front lines and the lack of accessible care for patients. BCC was made to solve these challenges by providing high-quality telemedicine that allows patients to perform self-diagnosis from the comfort of their own homes. This not only reduces the number of instances in which doctors come into contact with contagious patients but also allows hospitals to utilize resources more efficiently for improved healthcare overall.
By utilizing the COUGHVID database, with more than 2,000 sample sounds, to train an AI model in PictoBlox’s machine learning environment, our system has an accuracy of over 90%. With the addition of a symptom survey, which asks users about signs such as fatigue, loss of taste, and shortness of breath, the diagnostic accuracy increases even more. The implementation of a cute bear in the user interface increases engagement and aligns with the Codeavour spirit!, with added severe covid detection.
Our project aims to advance the fields of innovation and medicine by contributing valuable cough sound data to expand the global database and inspire future innovators!
HELPING HANDS
The aim of my project is to lend a prosthetic hand to friends without hands to help them in doing everyday activities in a smooth way.
In my project, I have made a prosthetic hand using some untearable paper and EEG [Electroencephalogram] CHIP PWX. The fingers of the prosthetic hand are made of cut acrylic and move with the help of the pipe cleaning wires that spring them back and forth. The 5 servo motors pull the wires to make the hand move. There is An Arduino Uno Board which is connected to a PWX Chip. The PWX Chip has wires that connect the GELS to the chip. When the GELS receive movement, it signals the PWX EEG chip which in turn signals the Arduino Uno. The Arduino is connected to the server motors which makes the movement of the motor.
The software used in making this project is PICTOBLOX and the code is typed in C++.
I have also worked with hard plastic by using a 3D pen to make it stronger and water proof in case of any emergency and for regular usage.
IN WHAT WAYS IS MY PROJECT GOING TO HELP FRIENDS IN NEED?
The project that I have made is helping friends and other people without hands to help them do daily chores and activities with ease. The usage of batteries has made my project easily accessible by anyone from anywhere.