Keqi Wu, Chengliang Fan, Minfeng Tang, Hongyu Chen, Yajia Pan, Dabing Luo and Zutao Zhang
{"title":"Symbiotic energy-sensing wind generator enabled AI for smart roads†","authors":"Keqi Wu, Chengliang Fan, Minfeng Tang, Hongyu Chen, Yajia Pan, Dabing Luo and Zutao Zhang","doi":"10.1039/D5SE00510H","DOIUrl":null,"url":null,"abstract":"<p >Various monitoring devices have been installed on roads to capture traffic conditions, with electricity being essential for the operation of these devices. To reduce reliance on traditional power sources, this paper proposes a symbiotic energy-sensing dual wind cup triboelectric electromagnetic hybrid generator (DW-TEHG). Its dual wind cup enhancement mechanism (EM) converts wind energy into kinetic energy, which drives the electromagnetic generator (EMG) to operate efficiently. The wind speed monitoring unit perceives wind speed through voltage output, while an energy management unit is responsible for energy storage and power supply to sensing devices. Experiments have optimized the matching parameters of the dual wind cups, enhancing the output capability by 153% compared to a single wind-cup design. Additionally, at a wind speed of 5 m s<small><sup>−1</sup></small>, the DW-TEHG can achieve a maximum output power of 92.48 mW, capable of charging a 0.1 F capacitor to 12 V. Furthermore, wind speed monitoring based on artificial intelligence (AI) is implemented, with an average recognition rate of 99.85%. Combined with digital twin technology and 5G communication, it enables visual environmental monitoring. These results demonstrate the huge potential of the DW-TEHG for road applications that can contribute to the development of smart transportation.</p>","PeriodicalId":104,"journal":{"name":"Sustainable Energy & Fuels","volume":" 15","pages":" 4146-4163"},"PeriodicalIF":5.0000,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sustainable Energy & Fuels","FirstCategoryId":"88","ListUrlMain":"https://pubs.rsc.org/en/content/articlelanding/2025/se/d5se00510h","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CHEMISTRY, PHYSICAL","Score":null,"Total":0}
引用次数: 0
Abstract
Various monitoring devices have been installed on roads to capture traffic conditions, with electricity being essential for the operation of these devices. To reduce reliance on traditional power sources, this paper proposes a symbiotic energy-sensing dual wind cup triboelectric electromagnetic hybrid generator (DW-TEHG). Its dual wind cup enhancement mechanism (EM) converts wind energy into kinetic energy, which drives the electromagnetic generator (EMG) to operate efficiently. The wind speed monitoring unit perceives wind speed through voltage output, while an energy management unit is responsible for energy storage and power supply to sensing devices. Experiments have optimized the matching parameters of the dual wind cups, enhancing the output capability by 153% compared to a single wind-cup design. Additionally, at a wind speed of 5 m s−1, the DW-TEHG can achieve a maximum output power of 92.48 mW, capable of charging a 0.1 F capacitor to 12 V. Furthermore, wind speed monitoring based on artificial intelligence (AI) is implemented, with an average recognition rate of 99.85%. Combined with digital twin technology and 5G communication, it enables visual environmental monitoring. These results demonstrate the huge potential of the DW-TEHG for road applications that can contribute to the development of smart transportation.
期刊介绍:
Sustainable Energy & Fuels will publish research that contributes to the development of sustainable energy technologies with a particular emphasis on new and next-generation technologies.