Wearable MCU Serial Integration With Asynchronous Sensor Transfer
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Solution Overview
Problem
Wearable devices face high power consumption due to synchronous data transfer from sensors to microcontroller units (MCUs), which is exacerbated by increased data volumes and sensor integration, leading to reduced battery life.
Innovation Solution
Implementing asynchronous data transfer techniques where the MCU remains inactive during data transfer from sensors to memory, using hardware components to read and write data to RAM without activating the MCU core, thereby reducing power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If synchronous data transfer is used from sensors to MCU, then data can be transferred reliably, but power consumption increases significantly
Solution Approach 1:
The data transfer process is segmented into two distinct phases: an asynchronous data collection phase where sensors dump data to memory without MCU intervention, and a scheduled processing phase where the MCU wakes up to read and process the accumulated data. This segmentation allows the MCU to remain inactive during data collection, significantly reducing power consumption while maintaining data transfer reliability through the structured two-phase approach.
Solution Approach 2:
Data is collected and stored in memory beforehand by the sensor system in an asynchronous manner, preparing the data for later processing. The MCU then wakes up only when needed to read this pre-collected data. This preliminary action of data collection before MCU activation eliminates the need for the MCU to be continuously awake during data transfer, resolving the contradiction between reliable data transfer and low power consumption.
2Adaptability or versatility
If data volume increases from multiple sensors, then more comprehensive data collection is achieved, but transfer time and power consumption increase
Solution Approach 1:
Multiple sensors independently collect and store their data in memory beforehand in an asynchronous manner, accumulating comprehensive data from all sensors without requiring the MCU to be awake. The MCU then wakes up once to process all accumulated data. This preliminary action allows the system to handle increased data volume from multiple sensors efficiently, as the time-consuming data collection is performed before the MCU activates, thereby reducing the perceived transfer time from the MCU's perspective.
Solution Approach 2:
The sensor system continuously collects and stores data in memory without interruption or MCU intervention, maintaining continuous useful action during the inactive period. This continuous asynchronous data collection allows the system to accumulate comprehensive data from multiple sensors efficiently, and when the MCU wakes up, all data is already ready for processing, effectively reducing transfer time despite increased data volume.
3Adaptability or versatility
If more sensors are integrated into the wearable device, then functionality and data collection capability improve, but device complexity and power consumption increase
Solution Approach 1:
The system architecture is segmented into independent sensor modules that operate autonomously to collect and store their data, and a separate MCU processing module that handles data processing only when activated. This segmentation allows multiple sensors to be integrated without increasing the complexity burden on the MCU, as each sensor operates independently in the asynchronous phase. The MCU's role is simplified to reading pre-collected data, making the system scalable with additional sensors while managing complexity.
Solution Approach 2:
Memory acts as an intermediary between the sensors and the MCU, buffering data from multiple sensors before the MCU processes it. This intermediary allows the system to integrate more sensors without directly increasing MCU complexity, as the memory layer absorbs the data management overhead. The MCU simply reads from memory rather than directly coordinating with multiple sensors, thereby managing system complexity while supporting enhanced sensor integration capability.
Data Source
AI summary
Methods, systems, and devices for automated serial device integration to a microcontroller unit (MCU) of a wearable device are described. Hardware (HW) components of the MCU of the wearable device may receive an interrupt command from sensors of the wearable device via one or more buses during a time interval that processing components of the MCU are in an inactive state. The HW components may perform a read operation to read data from a preconfigured buffer address of the sensors during the time interval that the one or more processing components are in the inactive state and based on receiving the interrupt command. The HW components may then perform a write operation to write the data to a preconfigured memory address of the memory during the time interval that the one or more processing components are in the inactive state.