Power budget
Sampling, processing, radio activity, and user experience all had to fit within a constrained wearable battery profile.
Honeywell
Wearable Smart Patch
A connected medical wearable platform for continuous monitoring, secure communication, and reliable cloud-assisted product operation.
Embedded CESP32Bluetooth LESensorsSecure CommunicationIoT
Case Study
Overview
The smart patch combined low-power sensing, embedded firmware, wireless connectivity, and cloud integration in a wearable form factor.
The product architecture emphasized dependable data acquisition, power efficiency, secure communication, and traceable engineering decisions.
- Domain
- Medical Devices
- Connectivity
- Bluetooth Low Energy
- Focus
- Low Power & Reliability
- Lifecycle
- Product Development
Context
Problem Statement
Provide continuous monitoring from a compact wearable while balancing battery life, signal quality, comfort, and connectivity.
Create a dependable device-to-cloud data path suitable for a product with strong quality and security expectations.
Leadership
My Role
- Supported product architecture and cross-functional engineering planning.
- Reviewed embedded firmware structure, connectivity behavior, and product risks.
- Aligned device, mobile, cloud, verification, and manufacturing stakeholders.
- Drove design reviews focused on reliability, security, and product readiness.
Platform
Technology Stack
Core technologies and engineering disciplines used across the product.
- Embedded C
- ESP32
- Bluetooth LE
- Sensors
- Secure Communication
- IoT
- Cloud APIs
- OTA
System Design
Architecture
The architecture separates sensing and signal acquisition from device control, secure BLE transport, companion connectivity, and cloud services.
Architecture overview
- Sensors
- Acquisition Firmware
- Device Services
- Secure BLE
- Companion Gateway
- Cloud Platform
Execution
Engineering Challenges
Data integrity
Temporary connectivity loss could not result in silent gaps or ambiguous device state.
Cross-system verification
Firmware, mobile connectivity, and cloud behavior needed one traceable end-to-end test strategy.
Trade-offs
Key Decisions
Event-driven firmware
Used explicit operating states and scheduled radio activity to make power behavior measurable and testable.
Store-and-forward data
Buffered important records locally so intermittent connectivity did not compromise continuity.
End-to-end observability
Defined identifiers and diagnostics that allowed device events to be traced through the connected system.
Impact
Results
- Created a clearer platform boundary between sensing, connectivity, and cloud concerns.
- Made battery and connectivity behavior measurable through explicit engineering budgets.
- Improved cross-functional reviews with end-to-end data-flow and failure-mode analysis.
- Established a scalable basis for future wearable variants.
Reflection
Lessons Learned
- Power optimization works best when every subsystem owns a measurable budget.
- Connected medical products need end-to-end traceability, not isolated component tests.
- Offline behavior should be treated as a normal operating mode rather than an exception.