Continuous Iteration
Software Engineering
Solution Architecture
Prototyping and validation

Predicting and Preventing Childhood Asthma Attacks with Albus Health

Software Engineering

Develop a seamless, non-invasive respiratory monitoring system to predict and prevent serious asthma attacks in children.

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Building on the momentum of a successful partnership with Amazon Web Services, we were introduced to Albus Health, a pioneering company focused on childhood asthma. Albus Health's innovative approach combines radar particulate matter sensors and audio sensors to create a respiratory monitoring system. These sensors are designed to detect early signs of asthma attacks, enabling timely and preventive interventions.

Our challenge was to develop a solution that integrates seamlessly into the daily lives of patients without causing disruption.

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To address this challenge, we emphasised data management, system security, and user engagement.

Key elements included a robust study management system for secure cloud transmission, participant management, and real-time monitoring. Using Yocto and Mender for OTA updates, we ensured continuous improvements, rigorous testing, and health checks for reliability and smooth operation.

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The solution was a comprehensive study management system that integrated data from Albus Health's respiratory monitoring devices into the cloud. Key features of this solution included:

  • Cloud Integration - Leveraging AWS IoT and Mender, we ensured seamless updates and efficient data management. This cloud-based approach facilitated real-time monitoring and data analysis.
  • Data Security - We implemented robust encryption and authentication mechanisms to safeguard sensitive health data. These security measures were critical in maintaining the confidentiality and integrity of patient information.
  • User Involvement - Throughout the project, we maintained close collaboration with Albus Health and the feedback from study participants and third parties. Daily progress updates and collaborative decision-making processes kept them engaged and ensured that the solution met their needs and expectations.
  • Scalability - The system was designed to scale, accommodating an increasing number of devices and data points as the study expanded. This scalability was essential for the long-term success and impact of the project.

We are enthusiastic about the future of Albus Health and proud to contribute to such a significant technical discovery. Our goal for the next three years is to develop a bedside IoT device and a mobile app to monitor breathing during the night. By pre-empting severe asthma episodes, these innovations aim to significantly improve the quality of life for children with asthma.

The seamless integration of advanced monitoring technologies into everyday life has the potential to save lives and enhance the well-being of countless children.

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