Figure 1: Low-power sensor modes for design efficiency (Source)

The most direct method for achieving low power consumption in sensor design is incorporating lower power states such as shutdown and low-power operating modes. This allows system designers to directly control the sensor’s operation directly, offering significant power savings, as shown in Figure 1.

Efficient data processing techniques

a) On-sensor data processing: This reduces power consumption by minimizing data transmission, decreasing the load on central processors, enabling more effective power management, and reducing the need for high-power infrastructure. On-Sensor data processing leads to significant energy savings and improved system efficiency, especially in battery-powered and remote applications.

b) Integrating an MCU with the sensor: Integrating an MCU with sensors allows for local computation, reducing power consumption by offloading tasks from the main processor. This approach enables complex computations directly on the MCU, which consumes significantly less power than the main system processor. For example, in a fitness tracker, continuous monitoring can strain a smartphone's battery, but using a dedicated MCU for local processing ensures efficient operation without draining the main device. This strategy preserves battery life by keeping the primary processor and other components in low-power states when not actively processing sensor data. Integrating sensor functions with an MCU optimizes energy usage, making applications more sustainable and extending device battery life.

Reducing sensor power consumption through power-efficient communication

Reducing sensor power consumption through power-efficient communication is vital for extending the operational lifespan of devices. Significant energy savings can be achieved by optimizing data transmission methods and employing low-power communication protocols.

• Minimized Data Transmission: Techniques like data compression and aggregation reduce the data volume, decreasing the power needed for communication.
• Lower Transmission Frequency: Event-driven and scheduled transmissions limit the frequency of data sent, saving energy by keeping sensors in low-power states longer.
• Efficient Communication Protocols: Low-power protocols such as Zigbee and BLE and adaptive protocols that adjust transmission parameters reduce energy usage.
• Optimized Radio Usage: Shorter transmission times and low-power radio modes reduce active periods and power consumption.
• Energy-Efficient Hardware: Low-power transceivers and energy harvesting further reduce power needs.
• Improved Network Efficiency: Efficient network topologies and smart routing reduce transmission power and frequency.
• Reduced Overhead: Streamlined protocols and optimized payload sizes minimize unnecessary data transmissions, saving energy.
• Lower Signal Strength: Adaptive signal power and proximity-based communication ensure efficient energy use for data transfer.

Minimize leakage currents

Minimizing current leakage in sensor design is essential for enhancing energy efficiency and extending battery life. This can be achieved by:

• Using low-leakage components, such as specialized CMOS technologies and precision resistors.
• Optimizing circuit design to reduce node capacitance and isolate high-impedance nodes.
• Selecting low-leakage transistors and employing advanced techniques like body biasing in integrated circuits.
• Implement proper PCB design and use high-quality materials with adequate grounding and shielding techniques.
• Utilizing low-leakage power supplies and optimizing sensor interfaces.
• Applying advanced leakage reduction methods like reverse biasing and adaptive control.
• Regular testing and validation ensure these strategies are effectively implemented across varying environmental conditions.

Implement Power Gating Switches

Power Gating Transistors (usually PMOS or NMOS) can be used as switches to disconnect the power supply to specific blocks when idle. Design control signals to activate or deactivate these switches based on the sensor's operational state.

Software optimization

Optimize code, use predictive power management, and enable context-aware operation to tailor sensor activity and minimize power consumption. This ensures longer battery life and enhanced energy efficiency.

Modular design

Employing a modular design can help sensors achieve low power consumption by enabling selective activation, efficient integration, dynamic adaptation, and targeted power management. This approach simplifies component upgrades and maintenance, minimizes complexity, improves isolation, and allows for precise control of power supplies. The result is an energy-efficient, scalable, and flexible sensor system optimized for low-power operation.

Thermal management

Efficient thermal management in sensor design is critical for minimizing power consumption and optimizing performance. Key benefits include:

• We are reducing energy waste and maintaining optimal operational temperatures by preventing overheating.
• Ensuring sensors operate efficiently without excessive power usage.
• We are enhancing reliability by stabilizing performance and preventing thermal drift, which could affect accuracy and necessitate recalibration.
• Extending sensor lifespan by maintaining optimal temperature ranges and reducing power consumption associated with frequent replacements.
• Lowering the need for active cooling systems like fans, thus decreasing overall energy use in the sensor system.
• Preserving sensitivity and accuracy by stabilizing thermal conditions, minimizing the need for power-intensive compensations or recalibrations.

Effective enclosure design and heat sink integration further contribute to energy efficiency by stabilizing internal temperatures and dissipating excess heat, thereby reducing thermal stress and overall power consumption in sensor operations.

Sensor hub, use case example, based on i.MX 8ULP applications processors

Ultra-low power management subsystem: Supports long battery life with efficient power processing.

Sensor hub: Demonstrates deep sleep and wake-up transitions with minimal power consumption.

Evaluation kit for power measurement: Includes tools for power analysis with both GUI and command-line interfaces.

Figure 2: A system comprising of i.MX 8ULP, display and sensor hub (Source)

The i.MX 8ULP features an Energy Flex architecture, which includes the Application, Flex, and Real-Time domains. Its specialized power management system supports various power modes to optimize power consumption, as shown in Figure 3.