IoT-Based Airport Noise Perception and Monitoring: Multi-Source Data Fusion, Spatial Distribution Modeling, and Analysis DOI Creative Commons
Jing Liu, Shaotong Sun, Ke Tang

et al.

Sensors, Journal Year: 2025, Volume and Issue: 25(8), P. 2347 - 2347

Published: April 8, 2025

With the acceleration of global urbanization, airport noise pollution has emerged as a significant environmental concern that demands attention. Traditional monitoring systems are fraught with limitations, including restricted spatial coverage, inadequate real-time data acquisition capabilities, poor correlation, and suboptimal cost-effectiveness. To address these challenges, this paper proposes an innovative perception approach leveraging Internet Things (IoT) technology. This method integrates multiple streams, encompassing noise, meteorological, ADS–B data, to achieve precise event tracing deep multi-source fusion. Furthermore, study employs Kriging interpolation Inverse Distance Weighting (IDW) techniques perform on from sparse sites, thereby constructing distribution model noise. The results practical application demonstrate proposed can accurately reflect spatiotemporal patterns effectively correlate events, providing robust support for development control policies.

Language: Английский

Advanced Sensor Technologies in CAVs for Traditional and Smart Road Condition Monitoring: A Review DOI Open Access

Masoud Khanmohamadi,

Marco Guerrieri

Sustainability, Journal Year: 2024, Volume and Issue: 16(19), P. 8336 - 8336

Published: Sept. 25, 2024

This paper explores new sensor technologies and their integration within Connected Autonomous Vehicles (CAVs) for real-time road condition monitoring. Sensors like accelerometers, gyroscopes, LiDAR, cameras, radar that have been made available on CAVs are able to detect anomalies roads, including potholes, surface cracks, or roughness. also describes advanced data processing techniques of detected with sensors, machine learning algorithms, fusion, edge computing, which enhance accuracy reliability in assessment. Together, these support instant safety long-term maintenance cost reduction proactive strategies. Finally, this article provides a comprehensive review the state-of-the-art future directions monitoring systems traditional smart roads.

Language: Английский

Citations

4
Independent Dual-Mode Humidity and Hydrogen Detection Using a Plasmonic-Photonic Hybrid Metasurface DOI
Hongsen Zhao, Qiushun Zou,

Ang Xu

et al.

ACS Applied Optical Materials, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 27, 2025

Language: Английский

Citations

0
IoT-Based Airport Noise Perception and Monitoring: Multi-Source Data Fusion, Spatial Distribution Modeling, and Analysis DOI Creative Commons
Jing Liu, Shaotong Sun, Ke Tang

et al.

Sensors, Journal Year: 2025, Volume and Issue: 25(8), P. 2347 - 2347

Published: April 8, 2025

With the acceleration of global urbanization, airport noise pollution has emerged as a significant environmental concern that demands attention. Traditional monitoring systems are fraught with limitations, including restricted spatial coverage, inadequate real-time data acquisition capabilities, poor correlation, and suboptimal cost-effectiveness. To address these challenges, this paper proposes an innovative perception approach leveraging Internet Things (IoT) technology. This method integrates multiple streams, encompassing noise, meteorological, ADS–B data, to achieve precise event tracing deep multi-source fusion. Furthermore, study employs Kriging interpolation Inverse Distance Weighting (IDW) techniques perform on from sparse sites, thereby constructing distribution model noise. The results practical application demonstrate proposed can accurately reflect spatiotemporal patterns effectively correlate events, providing robust support for development control policies.

Language: Английский

Citations

0