An AI-first sleep improvement app that combines advanced algorithms with IoT devices to address issues like insomnia, early waking, and disrupted sleep.
AI models analyze sound detection (snoring, sleep talking, ambient noise) and a 2-week sleep diary to provide personalized insights, dream analysis, and tailored recommendations.
IoT integration with smart masks and wearables (Apple/Android watches) tracks SpO? in real time, triggering vibration alerts to prevent oxygen drops and support early OSA intervention.
Users can connect with sleep experts via AI-enabled chat, audio, and video, while providers manage appointments and communications through a dedicated web interface.
The platform follows a subscription model with free and premium tiers, enabling sleep diagnostic centers to deliver AI-driven insights, IoT monitoring, and expert support for better sleep health.

The app aims to help individuals with sleep issues like difficulty falling asleep, waking up too early, or trouble resuming sleep by analyzing sleep sounds through the device’s microphone. It will leverage AI to classify sleep sounds, detect snoring, and assess sleep apnea risk, providing personalized insights and recommendations. Using AI-driven analysis, the app will offer real-time reports and track sleep patterns, all while functioning offline. Additional features include meditation videos, sleep tracking, and relaxation tools to improve sleep hygiene.

This project focused on creating mapping reports to highlight geographic and linguistic disparities in OB/GYN service availability across Kansas. The objective was to provide visual evidence for healthcare researchers and policymakers to better understand provider distribution, identify underserved regions, and highlight language access barriers for Hispanic populations. The deliverables included static maps of provider clusters, Spanish-speaking access segmentation, and a custom symbolic visual to humanize the access challenge.