Recon Health utilizes Edge Computing and embedded Artificial Intelligence to facilitate remote patient monitoring. This technology enables real-time health data collection and analysis, improving patient outcomes and reducing the need for in-person visits.
Funding
Funding not disclosed
Founders
Product
Problem
Remote patient monitoring often requires reliable, real-time data processing and analysis, which can be challenging in areas with limited network connectivity. Traditional systems may struggle to efficiently handle large volumes of patient-generated health data, leading to delays in critical alerts and interventions.
Solution
Recon Health provides a remote patient monitoring solution leveraging edge computing and embedded AI to enable real-time health data collection and analysis, even in areas with poor network connectivity. By processing data locally on edge devices, the system reduces latency and ensures timely alerts for critical health events. The embedded AI algorithms analyze patient data in real-time, identifying patterns and anomalies that may require immediate attention. This approach improves patient outcomes by enabling proactive interventions and reducing the need for frequent in-person visits.
Target Audience
The primary target audience includes healthcare providers, hospitals, and remote patient monitoring service companies seeking to improve patient outcomes and reduce healthcare costs.
Features
- Edge computing architecture for local data processing and real-time analysis
- Embedded AI algorithms for anomaly detection and predictive analytics
- Secure data transmission to cloud-based platform for long-term storage and analysis
- Customizable alert thresholds and notification settings for personalized patient care
- Integration with wearable sensors and medical devices for continuous health data collection