Wake-Up Radio Control for Wireless Devices Using Predicted Sensor Data
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Solution Overview
Problem
IoT devices often wake up and transmit data unnecessarily, leading to quicker depletion of battery resources and undermining energy efficiency due to inefficient power management strategies.
Innovation Solution
Implement a system with a wake-up logic that compares predicted sensor data with actual sensor data to determine whether to switch the transceiver from sleep mode to wake mode, using a machine learning model trained on historical data to predict sensor data and minimize unnecessary wake-ups.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If IoT devices wake up and transmit data during every target wake time, then data transmission reliability is improved, but energy consumption increases and battery life decreases
Solution Approach 1:
The system performs preliminary actions by receiving and storing predicted sensor data before the scheduled wake time. During the wake time, the device compares actual sensor data with previously received predicted data to determine whether transmission is necessary, thereby avoiding unnecessary wake-ups and energy consumption while maintaining data transmission reliability when needed.
Solution Approach 2:
The system implements feedback by comparing actual sensor data with predicted sensor data. This comparison mechanism provides feedback on whether the predicted data accurately represents the current state, enabling the device to make informed decisions about whether to wake up and transmit data, thus balancing reliability with energy efficiency.
2Loss of energy
If IoT devices operate in sleep mode to conserve energy, then energy efficiency is improved, but data transmission responsiveness deteriorates
Solution Approach 1:
The network device performs preliminary actions by predicting sensor data in advance and transmitting these predictions to the IoT device before the scheduled wake time. This allows the IoT device to remain in sleep mode longer while still having access to predicted data, improving energy efficiency without significantly compromising transmission responsiveness when actual data differs from predictions.
Solution Approach 2:
The system dynamically adjusts the wake-up behavior based on the comparison between predicted and actual sensor data. When predictions are accurate, the device remains in sleep mode longer; when predictions deviate beyond a threshold, the device wakes up to transmit actual data. This dynamic adaptation optimizes both energy efficiency and transmission responsiveness.
3Ease of operation
If IoT devices use traditional power management with fixed target wake times, then operational simplicity is maintained, but energy efficiency deteriorates due to unnecessary wake-ups
Solution Approach 1:
The system maintains operational simplicity by keeping the fixed target wake time schedule while adding a preliminary action: receiving and storing predicted sensor data before each wake time. This preliminary step enables the device to evaluate whether waking up is necessary, improving energy efficiency without complicating the basic operational structure.
Solution Approach 2:
The IoT device performs self-service by autonomously comparing its actual sensor data with received predicted data and making independent decisions about whether to wake up and transmit data. This self-service mechanism improves energy efficiency without requiring complex external control systems, maintaining operational simplicity.
Data Source
AI summary
Devices, networks, systems, methods, and processes for facilitating power conservation in wireless devices are described herein. An access point (AP) in a wireless network may predict sensor data associated with a wireless device based on historical sensor data and various parameters associated with the wireless device. The AP predicts the sensor data when a transceiver of the wireless device is operating in a sleep mode. A wake-up radio of the wireless device that consumes less power than the transceiver is awake when the transceiver is operating in the sleep mode. The AP transmits the predicted sensor data to the wake-up radio. The wake-up radio maintains the transceiver in the sleep mode in response to the predicted sensor data deviating from actual sensor data, that is generated by a sensor of the wireless device, below a threshold value, thereby conserving power of the wireless device.