Tushar Gatthewar
ParticipantTushar Gatthewar
"Intelligent Bio-Monitoring Assistance System for Astronauts"
"Intelligent Bio-Monitoring Assistance System for Astronauts"
Individual
April 29, 2025 at 05:30 AM
Project Demo
Technology Stack
🔹 EEG-based Brain Activity Analysis – Using Deep Learning (CNN, LSTMs) for interpreting brain signals. 🔹 Eye Tracking & Movement Analysis – Implemented with OpenCV, MediaPipe, and Gaze Detection Models. 🔹 Voice Analysis & Sentiment Detection – Leveraging DeepSpeech, Whisper AI, and NLP models for speech recognition and emotional analysis. 🔹 Multi-Agent AI System – Built using Reinforcement Learning and Multi-Agent Systems for adaptive decision-making. 🔹 Edge AI & Deployment – Running models efficiently on Jetson Nano / Raspberry Pi for real-time inference in space environments. 🔹 Cloud & Data Handling – Utilizing AWS / Google Cloud for data storage, processing, and visualization.
Submission Details
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createdAt
04-02-2025 23:47
name
Tushar Gatthewar
linkedIn-profile
Project Title
"Intelligent Bio-Monitoring Assistance System for Astronauts"
Describe what your project does?
Our project is an Intelligent Bio-Monitoring Assistance System for Astronauts 🚀.
It uses multiple AI agents to constantly monitor an astronaut’s brain activity, eye movement, and voice patterns to understand their mental and physical state in space. Based on this data, the system provides real-time assistance, alerts, and recommendations to help astronauts stay healthy, focused, and perform better during missions.
Think of it as a smart AI co-pilot that keeps an eye on an astronaut’s well-being and supports them in deep space!
What AI tools did you use?
🔹 EEG-based Brain Activity Analysis – Using Deep Learning (CNN, LSTMs) for interpreting brain signals. 🔹 Eye Tracking & Movement Analysis – Implemented with OpenCV, MediaPipe, and Gaze Detection Models. 🔹 Voice Analysis & Sentiment Detection – Leveraging DeepSpeech, Whisper AI, and NLP models for speech recognition and emotional analysis. 🔹 Multi-Agent AI System – Built using Reinforcement Learning and Multi-Agent Systems for adaptive decision-making. 🔹 Edge AI & Deployment – Running models efficiently on Jetson Nano / Raspberry Pi for real-time inference in space environments. 🔹 Cloud & Data Handling – Utilizing AWS / Google Cloud for data storage, processing, and visualization.
Share a 3–5 minute demo video (Google Drive link only) explaining your core idea, tools used, challenges faced, and how you improved your solution — make sure the link is viewable.
Is this project your original and proprietary work?
Yes
Does it include any private, sensitive, or restricted code or content?
No
Do you give us (AI Demos) permission to feature your work on our website and share it with our community (with full credit)?
Yes
Do you consent to us showcasing your name/profile on our social media platforms and YouTube
Yes