AI and machine learning are transforming public health by enabling data-driven insights that improve decision-making, streamline resource allocation, and enhance disease prevention efforts. With predictive analytics, public health agencies can identify at-risk populations, anticipate outbreaks, and deploy targeted interventions.
Healthcare AI/ML
Flamelit brings a strong track record of delivering advanced analytics and data-driven solutions, with a focus on healthcare. Our collaboration with a leading Health Care research organization has yielded significant projects, such as the Pediatric Asthma Surveillance System (PASS), which identified pediatric asthma risk of emergency department visits by community for public health leaders and community organizers, implementing and operating several AI/ML models, trainings, and regularly recurring reporting for the COVID-19 Pandemic Response program and the Sepsis Present-on-Arrival AI model, where individual risk is automatically assessed for presence of Sepsis during emergency room/urgent care arrival.
AeroClarity
Dirty air is the "greatest external threat to public health" (CBS News) and requires increased monitoring at industrial facilities and communities. Current air monitoring sensors are expensive, require regular maintenance and physical installation - creating additional burden, processes, and bureaucracy for collecting regular high quality measurements. AeroClarity reduces the burden, process overhead, bureaucracy, and maintenance costs for ambient air quality monitoring. Additionally, AeroClarity offers superior resolution and temporal frequency compared to existing air monitoring solutions.
Flamelit is in the Research and Development phase of using CubeSat technologies, data science algorithms, and machine learning methods to improve quality and reduce costs of air quality remote sensing. AeroClarity provides ambient air quality monitoring requiring no install, maintenance, or manual labor. The difference is clear with our new approach to monitoring services.
