Pharma & Healthcare
IoT Health Monitoring Application Built for an Indian Multinational Healthcare Enterprise
Enabling large-scale health data collection, anomaly detection, and timely notifications
Comprehensive Health
Data Collection
Proactive Anomaly
Detection
Timely
Notifications
Client Overview
The client is an Indian multinational healthcare enterprise operating across multiple regions and care environments. With a growing focus on connected health devices, the organization required a centralized system to collect, process, and monitor health data at scale.
As device adoption increased, the need for reliable data ingestion, real-time analysis, and dependable notifications became critical. The organization partnered with Sthenos Technologies to develop an IoT-enabled application that supports these requirements while remaining scalable and resilient.
Challenge
- Scaling cloud infrastructure to handle fluctuating volumes of incoming IoT data
- Ensuring seamless integration with diverse IoT devices that collect health parameters
- Maintaining reliable notification delivery, including email and SMS alerts for anomalies
- Preserving data accuracy and continuity as the system scaled across environments
Our Approach
Sthenos designed an IoT application focused on scalability, reliability, and interoperability.
Unified Data Ingestion
The platform was built to collect health data from multiple IoT devices using standardized protocols, ensuring compatibility across device types and vendors.
Scalable Cloud Architecture
Cloud infrastructure was designed to dynamically scale based on data volume, supporting both routine monitoring and peak usage without performance degradation.
Real-Time Processing and Analysis
Incoming data was processed efficiently to identify deviations from expected thresholds, enabling early detection of potential health anomalies.
Reliable Notification Handling
The system ensured dependable delivery of alerts through multiple communication channels, minimizing the risk of missed or delayed notifications.
Technical Spotlight
- Cloud-Native Infrastructure: AWS Cloud provided a scalable and reliable foundation, enabling the application to automatically adjust resources based on incoming data loads.
- Efficient Application Development: Python was used to develop core services, supporting fast integration, readability, and maintainable logic for IoT workflows.
- Lightweight Messaging Protocols: MQTT enabled fast, low-latency communication between IoT devices and backend services, ensuring efficient data transfer.
- Reliable Notification Systems: Redundant notification mechanisms were implemented to ensure alerts were delivered consistently via email and SMS.
Solution Delivered
- Health data was collected and stored securely from connected devices
- The system continuously analyzed incoming data for anomalies
- Notifications were triggered automatically when thresholds were breached
- Cloud infrastructure scaled dynamically to support varying data volumes
Results
- Comprehensive health data collection across multiple IoT devices and environments
- Early identification of anomalies, supporting proactive intervention
- Timely delivery of notifications, improving response readiness
- Improved reliability and scalability of health data operations
Tech Stack
