Co-Processor Sensor Data Acquisition Mode Management
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Solution Overview
Problem
Modern mobile devices with multiple sensors face challenges in efficiently managing and synchronizing data acquisition modes across different sensors, leading to potential latency and power consumption issues, which can affect performance in various applications such as augmented reality and navigation.
Innovation Solution
A system and method where a processor receives requests for sensor data from multiple sensors, instructing them to operate in specific acquisition modes, such as triggered or free-running modes, to optimize data capture based on application needs, and synchronizes data timestamps for integration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple sensors operate in different acquisition modes simultaneously, then data acquisition efficiency and adaptability are improved, but system complexity and synchronization difficulty increase
Solution Approach 1:
The patent segments sensor management by creating a dedicated co-processor specifically for sensor data acquisition and processing, separating it from the main application processor. This allows independent control of multiple sensors in different acquisition modes (continuous, triggered, event-driven) without complicating the overall system architecture, as each sensor can be managed autonomously by the co-processor according to its specific requirements.
Solution Approach 2:
The co-processor acts as an intermediary between the sensors and the main processor. It receives sensor data in various acquisition modes, performs preliminary processing and synchronization, then delivers consolidated data to the application processor. This mediator approach simplifies the interface between diverse sensors and the main system, reducing overall complexity while maintaining flexible data acquisition.
2Loss of time
If sensor data acquisition is optimized for specific applications, then latency is reduced, but power consumption increases
Solution Approach 1:
The system dynamically adjusts sensor acquisition modes based on application requirements and device state. The co-processor can switch between continuous sampling (low latency but higher power), triggered sampling (balanced), and event-driven sampling (low power) modes for different sensors. This dynamic adaptation allows the system to minimize latency when needed while conserving power during normal operation, resolving the trade-off between these two parameters.
Solution Approach 2:
The patent changes operational parameters of sensors based on demand. The co-processor modifies sampling rates, acquisition modes, and data processing intensity according to application needs. For example, it can increase sampling frequency and reduce processing latency for time-critical applications, then decrease these parameters for power-saving mode, thereby adjusting the balance between latency and power consumption as required.
3Reliability
If all sensors operate in continuous acquisition mode, then data availability is improved, but power consumption and processing load increase
Solution Approach 1:
Instead of continuous acquisition for all sensors, the co-processor implements periodic sampling with variable intervals. Sensors can operate in continuous mode when data availability is critical, while other sensors use periodic sampling at optimized intervals based on their characteristics and application requirements. This periodic approach maintains sufficient data availability while dramatically reducing power consumption compared to universal continuous operation.
Solution Approach 2:
The co-processor enables sensors to operate autonomously in different acquisition modes based on their own characteristics and current conditions. Each sensor can self-regulate its operation (continuous, periodic, or event-triggered) under co-processor management, allowing the system to maintain data availability for critical sensors while letting non-critical sensors enter low-power states, thereby reducing overall power consumption while preserving necessary data availability.
Data Source
AI summary
Methods and systems for acquiring sensor data using multiple acquisition modes are described. An example method involves receiving, by a co-processor and from an application processor, a request for sensor data. The request identifies at least two sensors of a plurality of sensors for which data is requested. The at least two sensors are configured to acquire sensor data in a plurality of acquisition modes, and the request further identifies for the at least two sensors respective acquisition modes for acquiring data that are selected from among the plurality of acquisition modes. In response to receiving the request, the co-processor causes the at least two sensors to acquire data in the respective acquisition modes. The co-processor receives first sensor data from a first sensor and second sensor data from a second sensor, and the co-processor provides the first sensor data and the second sensor data to the application processor.