Addressing Power Issues in Biologging: An Audio/Inertial Recorder Case Study
Abstract
:1. Introduction
2. Hardware Architecture
2.1. System Overview
2.2. Sensors
2.3. Data Storage
2.4. MCU
3. Data Flow
- At the front end, an acquisition is performed by a sensor (transceiver) that transforms the physical input into raw digital data.
- At the back end, storage saves data into the non-volatile memory.
- In between, the data are processed to accommodate acquisition and storage formatting and to address global performance.
3.1. Data Acquisition
3.1.1. Microphone
3.1.2. Inertial Measurement Unit
3.2. Data Storage
3.3. Data Processing
3.3.1. Inline Audio Compression
3.3.2. Buffering Strategy
- First layer: A raw audio data buffer (32 bit samples) that is automatically filled by audio samples coming from the microphone-DFSDM-DMA hardware stream. It is labelled MIC buffer in Figure 6.
- Second layer: An ADPCM-compressed audio data buffer (4 bit samples). This buffer is filled by software every time the CPU performs ADPCM compression on raw audio samples. It is labelled ADPCM buffer in Figure 6.
- A simpler buffer scheme applies to inertial data with two additional buffers:
- An accelerometer data buffer (3 × 16 bit samples). This buffer is filled by the CPU every time an accelerometer interruption occurs.
- A magnetometer data buffer (3 × 16 bit samples). This buffer is filled by the CPU every time a magnetometer interruption occurs.
4. Firmware Tuning
4.1. Software Architecture
4.2. Dynamic Power Management Policy
- A “Capture” state during which (i) audio samples are collected and put into the MIC buffer with no CPU load, and (ii) the inertial sensor is performing its measure.
- A “Process” state during which the CPU is called for either (i) ADPCM compression, or (ii) inertial data reading and subsequent casual (iii) SD card writings.
- A “Standby” state that represents the deepest low-power state. It is the default state before and after a scheduled recording is performed. During this state, it is assumed that only minimal hardware resources are required to keep track of time and date (MCU’s Real-Time Clock (RTC)).
- The “Idle Hook” approach: The hook is a function called by the OS scheduler whenever it enters the idle task. The role of this hook is simply to disable unused peripherals and set the CPU in a sleep state. Exit from this state occurs upon any event (either a sensor interrupt or an OS event, including ticks). This method introduces very little overhead to the code execution. However, the CPU is still activated for a short time every OS tick so that it can be combined with an increase in tick periods.
- The “Tickless Idle” approach: It consists in preventing OS ticks to occur when there is no CPU load, which in practice means suspending execution of the OS scheduler. Doing so requires careful setup of extra mechanisms that (i) keep track of time during the tickless period instead of the OS and (ii) allow for exiting the idle state when an event requiring the CPU occurs. Expected events can be a sensor interruption or the end of a programmed delay. This approach introduces small execution overhead for entering and exiting the tickless mode.
4.3. Build Optimizations
4.4. CPU and Peripherals Clock Frequency
4.5. Standby Mode and Recorder Scheduler
5. Results
5.1. Audio Performances
5.2. Recorded Data Alignment
5.3. Battery Autonomy
5.4. Power Contributors
5.5. Related Works
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Version Name | fclk | FOSR | IOSR | Actual SR | Audio BW |
---|---|---|---|---|---|
8 kHz | 2 MHz | 32 | 8 | 7812.5 Hz | 3.9 kHz |
32 kHz | 64 | 1 | 31,250 Hz | 15.6 kHz |
Vsupply = 4.2 V | I (mA) | t (ms) | × | E (mJ) |
---|---|---|---|---|
Raw data | ||||
Sleep | 1.35 | 455.10 | 4 | 9.83 |
Process (roundoff) | 1.68 | 12.02 | 4 | 0.32 |
Store | 23.34 | 23.47 | 4 | 8.79 |
Total | 18.94 | |||
ADPCM | ||||
Sleep | 1.35 | 52.77 | 30 | 8.55 |
Process (encode) | 1.68 | 11.40 | 30 | 2.30 |
Store | 23.34 | 23.47 | 1 | 1.19 |
Total | 13.04 |
Data Buffers | Size | 73% |
---|---|---|
MIC Buffer | 39.5 kB | 30.8% |
ADPCM Buffer | 30 kB | 23.4% |
ACCL Buffer | 12 kB | 9.4% |
MAG Buffer | 12 kB | 9.4% |
Firmware | 11% | |
RTOS Heap | 11 kB | 8.6% |
Files management | 3.7 kB | 2.9% |
Miscellaneous | 2.4 kB | 1.87% |
Free | 17.4 kB | 16% |
Low-Power Mode | Tick Rate | Capture | Process | Average |
---|---|---|---|---|
None | 10 Hz | - | 1.6403 | 1.6403 |
None | 1 kHz | - | 1.6355 | 1.6403 |
None | 10 kHz | - | 1.6678 | 1.6403 |
Idle Hook | 10 Hz | 1.3210 | 1.6630 | 1.4855 |
Idle Hook | 1 kHz | 1.3301 | 1.6512 | 1.4907 |
Idle Hook | 10 kHz | 1.4733 | 1.6412 | 1.5986 |
Tickless Idle | 10 Hz | 1.3133 | 1.6567 | 1.4883 |
Tickless Idle | 1 kHz | 1.3247 | 1.6547 | 1.4905 |
Tickless Idle | 10 kHz | 1.3468 | 1.6350 | 1.5652 |
Optimization Level (gcc) | Capture (ms) | Process (ms) | Duty-Cycle | Supply Current (mA) |
---|---|---|---|---|
−O0 | 322 | 325 | 50.2 | 1.49 |
−O1 | 527 | 120 | 18.5 | 1.38 |
−O2 | 532 | 116 | 17.9 | 1.38 |
−O3 | 531 | 116 | 17.9 | 1.38 |
−Ofast | 531 | 115 | 17.9 | 1.38 |
Sampling Rate | Supply Voltage | Supply Current | Power | |
---|---|---|---|---|
This Work | 8 kHz | 3.8 V 1SLi-Ion | 1.97 mA | 7.5 mW |
32 kHz | 3.45 mA | 13.1 mW | ||
AudioMoth [16] | 8 kHz | 4.5 V (3 × AA) or 6 V | 10 mA | 45 mW |
32 kHz | 13 mA | 58 mW | ||
SOLO [11] | 16 kHz | 5 V | - | 350 mW |
Song Meter Micro [23] | 8 kHz | 4.5 V (3 × AA) | - | 63 mW |
32 kHz | 88 mW | |||
BAR-LT [24] | 16 kHz | 3.8 V 1S Li-Ion | 20.6 mA | 78 mW |
32 kHz | 22.6 mA | 86 mW |
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Miquel, J.; Latorre, L.; Chamaillé-Jammes, S. Addressing Power Issues in Biologging: An Audio/Inertial Recorder Case Study. Sensors 2022, 22, 8196. https://doi.org/10.3390/s22218196
Miquel J, Latorre L, Chamaillé-Jammes S. Addressing Power Issues in Biologging: An Audio/Inertial Recorder Case Study. Sensors. 2022; 22(21):8196. https://doi.org/10.3390/s22218196
Chicago/Turabian StyleMiquel, Jonathan, Laurent Latorre, and Simon Chamaillé-Jammes. 2022. "Addressing Power Issues in Biologging: An Audio/Inertial Recorder Case Study" Sensors 22, no. 21: 8196. https://doi.org/10.3390/s22218196
APA StyleMiquel, J., Latorre, L., & Chamaillé-Jammes, S. (2022). Addressing Power Issues in Biologging: An Audio/Inertial Recorder Case Study. Sensors, 22(21), 8196. https://doi.org/10.3390/s22218196