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.
مؤشر استهلاك الطاقة الكهربائية
يعمل المشروع كمؤشر للكمية استهلاك الطاقة في المنازل, حيث يقوم بإعلام الساكنين بمستوى استهلاكهم ( استهلاك ضعيف- متوسط- عالي – استهلاك عالي جدا) يقوم البرنامج بتحليل بيانات العداد الكهربائي للمنزل من خلال رمز QR الذي يحتوى على اليابانات اللازمة للبرنامج لتسهيل عملية ادخال البيانات و قرائتها من طرف نموذج تعلم الآلة.
قمنا باستخدام خاصية الذكاء الإصطناعي لتدريب البرنامج بواسطة بيانات خاصة بعدة منازل مع كمية استهلاكهم للطاقة.
Laser Weed AI
Laser Weed AI is an AI-powered robotic system designed to detect and remove weeds efficiently in agriculture. Using a Raspberry Pi with a Raspberry Pi Camera, it analyzes real-time images and identifies weeds through machine learning. A 5W Laser Module eliminates unwanted weeds with precision, reducing the need for chemical herbicides. The robot moves on a chassis powered by 4 Geared DC Motors, while conveyor belts help in weed removal. An Arduino UNO with an RF Module allows manual control when needed. The system is powered by 2 x 12V Lithium-ion Battery Packs, ensuring extended operation. This innovative solution minimizes labor, reduces chemical use, and promotes eco-friendly farming. With AI-driven automation, Laser Weed AI supports sustainable agriculture, enhances crop yields, and improves farming efficiency. By integrating technology with agriculture, it offers an advanced, environmentally friendly method for modern weed management, ensuring long-term benefits for farmers and healthier, chemical-free organic crops. 🚜🌱✨
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.
ML Based Solution to Pollution
Vehicular emissions contribute significantly to air pollution, releasing harmful soot particles that degrade air quality and pose serious health risks. Traditional emission control systems lack real-time monitoring for clogged filters, leading to inefficient maintenance and increased pollution. Additionally, captured soot is typically discarded as waste, missing an opportunity for sustainable reuse. There is a need for an innovative solution that not only detects filter clogging in real time but also repurposes soot into a valuable product, reducing environmental impact and promoting circular economy practices.
Industrial Automation
a project where characters move and interact with objects in a way that causes a shift in direction. Based on your description, I’ll create an image of a simple scene where characters are moving toward an object, but when they approach the object, the characters change direction but near to it.
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!
Automatic medication dispenser for the Elderly.
Source and Importance
Currently, Thailand is gradually transitioning into an aging society, leading to a continuous increase in the elderly population.Elderly people often need to take multiple medications regularly, but several issues arise, such as: Forgetting to take medications Taking the wrong dosage or at the wrong time Over-reliance on caregivers This system was developed to assist elderly individuals in taking their medications correctly and on time.
Objective
To create a medication dispenser for the elderly that works by scanning their face, providing reminders for on-time medication intake, and reducing the risks associated with forgetting or taking the wrong medication
Working Principle.
The medication dispenser for the elderly operates automatically by scanning their face through a reminder system and dispensing the medication according to the scheduled time. The working principles are as follows : Set medication time The set time is recorded in the system’s memory.Notify the elderly when it’s time to take medication. The system will send a reminder signal via sound, light, or vibration. Scan the face to dispense medication to the correct person. The elderly person stands in front of the scanner to receive medication corresponding to the person’s record. Confirm medication intake An infrared sensor detects whether the medication has been taken. If not, it will send another reminder within 10 minutes. In case of a medical emergency during the day, such as a headache, you can receive medicine by making a hand gesture. If you raise your hand with five fingers extended, the medicine will drop down for you to take.
Mr. Bawarchi
Bawarchi is an innovative web application designed to revolutionize the way people cook. Built using PictoBlox, it acts as a personal digital chef, providing smart recipe recommendations based on the ingredients users already have at home. This eliminates the hassle of searching for meal ideas and helps reduce food waste.