IoT platform for smart remote patient monitoring
About the client
Carepath Technologies GmbH offers a telemedicine solution that remotely monitors symptom-specific data in home settings, aiding physicians in diagnosing and treating chronic respiratory diseases.
The challenge
To help people with respiratory diseases who can't access clinics, our client set out to develop an edge AI patient monitoring device for remote cough sound recognition. For this product, they needed an end-to-end platform, including a cloud component, a web-based portal, and a mobile application, that would serve patients, doctors, and caregivers.
Delivered value
Solution
The Lemberg Solutions team delivered an end-to-end IoT platform, ensuring cybersecurity compliance. The platform was engineered around the unique requirements of continuous device data flows, production-ready cloud infrastructure, and AI workload hosting. This included scalable compute and automated deployments, along with monitoring, security, and infrastructure optimization.
Device integration
A core part of the solution was connecting the client's SBC-based gateway to the cloud platform. Our team established secure, reliable device provisioning and data transmission from the device to the cloud, then ingesting and processing the incoming data for AI model processing, data aggregation, and visual representation.
Cloud infrastructure
The design and optimization of the cloud infrastructure included sizing virtual machines for AI workloads, automating environment provisioning through Infrastructure as Code, and establishing CI/CD pipelines for reliable and repeatable deployments. Cloud monitoring and security controls, alongside automated data processing and scaling mechanisms, ensure secure handling of growing volumes of patient-generated data and device traffic.
Backend and business logic
Our team built the backend that powers the platform — handling data ingestion from the device, processing it, and serving it to the web portal and mobile app. The advanced logic turns the raw data from the device into clinical value for doctors, caregivers, and patients.
Remote patient monitoring for clinicians and patients
The platform connects clinicians, allowing them to monitor patient states remotely, and patients, enabling tracking their own symptom trends.
Data collection, dashboards, and alerts for AI-powered patient monitoring
The platform supports data collection and notifications. The dashboards are backed by databases that store information interpreted from patients' cough sounds using AI algorithms.
Convenient and user-friendly mobile app
A mobile application enables patients to set up the device without assistance and view their symptom trends on a smartphone.
Web portal for clinicians
A web-based portal allows caregivers to monitor patient states remotely, as well as receive notifications and alerts.
QA validation, performance, and scalability testing
Together with the client, we compiled thorough test cases to run rigorous validation testing across QA, development, stage, and production environments — to ensure the device withstands peak loads after deployment to production.
The final solution spans both the edge and the cloud. At later stages, we helped the client optimize the platform infrastructure in the cloud. We also analyzed and suggested how many virtual machines were necessary to run AI algorithms.
How it works
