Previous Projects From HackRPI X
Jump to PhotosFirst Place
DAVE
Aryash, Zachary Fernandes, Drew Bhavsar, Shamar Samuels
DAVE (Digital Assistant for Vision Enhancement) is an innovative project designed to assist people with vision impairments. Developed by a team of four, three of whom have personal experience with vision issues, DAVE aims to address the challenges faced by 2.2 billion people worldwide with vision impairments. The system uses a camera mounted on glasses to capture the user's surroundings, allowing users to interact with DAVE through voice commands. Users can ask DAVE to describe their environment or answer questions about their surroundings. The project utilizes Python for both frontend and backend, incorporating technologies such as LLaVA for multimodal processing, OpenAI's Whisper for speech recognition, and Google Text-to-Speech for verbal responses.
First Place
DAVE
Aryash, Zachary Fernandes, Drew Bhavsar, Shamar Samuels
DAVE (Digital Assistant for Vision Enhancement) is an innovative project designed to assist people with vision impairments. Developed by a team of four, three of whom have personal experience with vision issues, DAVE aims to address the challenges faced by 2.2 billion people worldwide with vision impairments. The system uses a camera mounted on glasses to capture the user's surroundings, allowing users to interact with DAVE through voice commands. Users can ask DAVE to describe their environment or answer questions about their surroundings. The project utilizes Python for both frontend and backend, incorporating technologies such as LLaVA for multimodal processing, OpenAI's Whisper for speech recognition, and Google Text-to-Speech for verbal responses.
Second Place
HealthChat
Michael Anderson
HealthChat, is an AI-powered Medical Search System designed to simplify the process of finding appropriate medical care. Using the Bing GPT4 Engine, HealthChat offers two main features: a chat function for answering medical questions and a physician matching service. The project was built as a complete Next.js application, leveraging modern web technologies such as React, TypeScript, and MaterialUI 5. HealthChat's innovative use of prompt engineering ensures consistent and accurate JSON data responses, making it easier for users to understand their medical issues and find suitable doctors quickly.
Second Place
HealthChat
Michael Anderson
HealthChat, is an AI-powered Medical Search System designed to simplify the process of finding appropriate medical care. Using the Bing GPT4 Engine, HealthChat offers two main features: a chat function for answering medical questions and a physician matching service. The project was built as a complete Next.js application, leveraging modern web technologies such as React, TypeScript, and MaterialUI 5. HealthChat's innovative use of prompt engineering ensures consistent and accurate JSON data responses, making it easier for users to understand their medical issues and find suitable doctors quickly.
PRHI Patient Safety
RPillPal: A Biometric Pill Dispenser
Dan Fiumara, Om Anavekar, Abdul Muizz, Amaan Qureshi
RPillPal is a biometric-based pill dispenser designed to help prevent opiate overdoses by ensuring accurate medication management at home. Developed as a solution for patients discharged from the hospital, it uses fingerprint data to verify patient identity and dispense the correct dosage based on doctor recommendations. The device connects directly with healthcare providers, enabling them to monitor patient progress and adjust treatment plans as needed. The machine itself is built with an Arduino UNO WiFi board, incorporating a keypad, OLED display, stepper motor, and piezo speaker to handle physical pill dispensing, and communicates with an online database via HTTP requests. The front end, built using Svelte, interacts with the database using the fetch API to send and receive data, offering seamless UI updates through its reactive features.
PRHI Patient Safety
RPillPal: A Biometric Pill Dispenser
Dan Fiumara, Om Anavekar, Abdul Muizz, Amaan Qureshi
RPillPal is a biometric-based pill dispenser designed to help prevent opiate overdoses by ensuring accurate medication management at home. Developed as a solution for patients discharged from the hospital, it uses fingerprint data to verify patient identity and dispense the correct dosage based on doctor recommendations. The device connects directly with healthcare providers, enabling them to monitor patient progress and adjust treatment plans as needed. The machine itself is built with an Arduino UNO WiFi board, incorporating a keypad, OLED display, stepper motor, and piezo speaker to handle physical pill dispensing, and communicates with an online database via HTTP requests. The front end, built using Svelte, interacts with the database using the fetch API to send and receive data, offering seamless UI updates through its reactive features.
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