Scientists from the Aerospace Information Research Institute (AIR) at the Chinese Academy of Sciences (CAS) have introduced an enhanced algorithm known as Dynamic Quantum Particle Swarm Optimization (DQPSO) to enhance the precision and dependability of pressure sensors utilized in the tracking and monitoring of wild migratory birds.
Image Credit: Jessica Rolletta/Shutterstock.com
The DQPSO algorithm focuses on optimizing the performance of a Radial Basis Function (RBF) neural network specifically tailored for temperature compensation. This groundbreaking study performed takes a comprehensive approach to tackle the challenge of sensor accuracy in fluctuating temperatures.
The study was reported in the Electronics journal on October 22nd, 2023.
The algorithm incorporates a temperature-pressure fitting model that encompasses crucial parameters such as the rate of temperature change and gradient reference terms. This model ensures the adaptability of pressure sensors to diverse environmental conditions, a critical requirement for monitoring the movements of wild migratory birds.
The innovation lies in the algorithm's unique loss function, considering both fitting accuracy and complexity. This strategy reinforces the resilience of pressure sensors, enabling them to provide reliable data amid complex temperature variations.
Calibration experiments were conducted to validate the algorithm's efficacy. Compared to commonly used commercial sensor algorithms, the pressure sensors, without the DQPSO algorithm, exhibited an average absolute error of 145.3 Pascals during dynamic temperature changes. However, with the implementation of the DQPSO algorithm, this error was significantly reduced to 20.2 Pascals.
The researchers further tested and confirmed the algorithm in an embedded environment, ensuring low-power consumption, high precision, and real-time pressure compensation during the tracking and monitoring of wild migratory birds.
This breakthrough opens up new avenues for comprehending and safeguarding the journeys of wild migratory birds.
Journal Reference:
Xie, J., et al. (2023). Dynamic Temperature Compensation of Pressure Sensors in Migratory Bird Biologging Applications. Electronics. doi.org/10.3390/electronics12204373.
Source: https://english.cas.cn/