Smart pavement is composed of a monitor network, communication network, data center, and energy supply system, and it requires reliable and efficient energy sources to power sensors and devices. The mechanical energy is wasted and dissipated as heat in traditional pavement; this energy can be reused to power low-power devices and sensors for smart pavement. Mechanical energy harvesting systems typically perform through electromagnetic, piezoelectric, and triboelectric methods. Among the different methods, electromagnetic harvesters stand out for their higher output power. However, current electromagnetic harvesters face challenges such as bulky designs, low power density, and high input displacement requirements. This study proposed a green electromagnetic harvester (GEH) based on up-frequency and a unidirectional rotation mechanism to harvest mechanical energy from the pavement. A prototype was designed and prepared. The influence of different parameters on the electrical performance of the harvester was studied by using an MTS test instrument and simulation methods. The results demonstrate that increasing the frequency and optimizing the magnetic array significantly enhances electrical output. The open-circuit voltage in the N-S mode is 3.1 times higher than that in the N-N mode. At a frequency of 9 Hz and a displacement of 3.0 mm, the open-circuit voltage of the GEH is 6.73 V, the maximum power output is 171.14 mW, the peak power density is 1277.16 W/m, and the voltage has almost no decay after 100,000 cycles. Further, the application of the GEH in charging sensors and capacitors was demonstrated, which indicates the potential of a GEH to power sensors for smart roads.
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http://dx.doi.org/10.3390/ma18040786 | DOI Listing |
Materials (Basel)
February 2025
School of Highway, Chang'an University, Xi'an 710064, China.
Smart pavement is composed of a monitor network, communication network, data center, and energy supply system, and it requires reliable and efficient energy sources to power sensors and devices. The mechanical energy is wasted and dissipated as heat in traditional pavement; this energy can be reused to power low-power devices and sensors for smart pavement. Mechanical energy harvesting systems typically perform through electromagnetic, piezoelectric, and triboelectric methods.
View Article and Find Full Text PDFPLoS One
February 2025
School of Highway, Chang'an University, Xi'an, Shaanxi, China.
The development of a smart expressway ensuring all-weather safe access represents the future trajectory of transportation infrastructure. A key task in this advancement is the precise prediction of water film depth (WFD) on road surfaces. Conventional WFD prediction models often assume constant grade and cross slope, an oversimplification that may affect predictive accuracy.
View Article and Find Full Text PDFSensors (Basel)
December 2024
School of Highway, Chang'an University, Middle Section of South Erhuan Road, Xi'an 710064, China.
Semi-rigid bases are widely used in road construction due to their excellent properties, high rigidity, and frost resistance, and they have been in service for many years. However, as the service life increases, the maintenance demands also grow, with traditional maintenance methods still being the primary approach. Based on a typical case using ground-penetrating radar (GPR) technology, this study explores the issue of cracks in semi-rigid bases and their impact on overlay layers.
View Article and Find Full Text PDFFront Public Health
December 2024
Department of Architectural Engineering, Dankook University, Yongin-si, Gyeonggi-do, Republic of Korea.
This study presents a novel approach to quantitatively assess the impact of flooring materials on walkability using Inertial Measurement Unit (IMU) sensors and Dynamic Time Warping (DTW) algorithm. Four common pavement materials (wood, asphalt, concrete block, and cement) were evaluated across five age groups (20-30, 30-40, 40-50, 50-60, and over 60 years) with 80 participants walking 1,200 m on each surface. IMU sensors attached to the lumbar region recorded acceleration and gyroscope data, which were then analyzed using DTW to quantify gait stability.
View Article and Find Full Text PDFSensors (Basel)
November 2024
UHasselt, The Transportation Research Institute (IMOB), Martelarenlaan 42, 3500 Hasselt, Belgium.
The quality of bicycle path surfaces significantly influences the comfort of cyclists. This study evaluates the effectiveness of smartphone sensor data and smart bicycle lights data in assessing the roughness of bicycle paths. The research was conducted in Hasselt, Belgium, where various bicycle path pavement types, such as asphalt, cobblestone, concrete, and paving tiles, were analyzed across selected streets.
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