Peter Mésároš, Jana Smetanková, Annamária Behúnová, Katarína Krajníková
{"title":"利用人工智能(AI)分析建筑业对碳足迹影响的潜力","authors":"Peter Mésároš, Jana Smetanková, Annamária Behúnová, Katarína Krajníková","doi":"10.1007/s11036-024-02368-y","DOIUrl":null,"url":null,"abstract":"<p>Construction is an important sector of human activity that significantly impacts the environment. The impact of this sector can be analysed from different perspectives, such as consumption of natural resources, waste generation, energy intensity, and environmental change. The sector is increasingly promoting using renewable materials, energy-efficient practices, and planning those respects ecological processes and biodiversity. Against this background, it is important to take coordinated action across the sector and move to net-zero carbon standards through immediate action to raise awareness, implement innovation, and improve carbon management and reporting processes. Tools supporting the reduction of the adverse impacts of construction activities include artificial intelligence tools. The construction industry has long been considered a conservative and traditional industry but is now experiencing a technological revolution. Gradually, artificial intelligence (AI) principles and tools are beginning to be integrated into the various lifecycle processes of construction projects. This paper analyses the AI tools used to analyse carbon footprinting in the construction sector in terms of selected functionalities. The results of the research will form the basis for the development of a strategic plan for the development of AI within the research activities at the Faculty of Civil Engineering in Košice.</p>","PeriodicalId":501103,"journal":{"name":"Mobile Networks and Applications","volume":"115 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The Potential of Using Artificial Intelligence (AI) to Analyse the Impact of Construction Industry on the Carbon Footprint\",\"authors\":\"Peter Mésároš, Jana Smetanková, Annamária Behúnová, Katarína Krajníková\",\"doi\":\"10.1007/s11036-024-02368-y\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Construction is an important sector of human activity that significantly impacts the environment. The impact of this sector can be analysed from different perspectives, such as consumption of natural resources, waste generation, energy intensity, and environmental change. The sector is increasingly promoting using renewable materials, energy-efficient practices, and planning those respects ecological processes and biodiversity. Against this background, it is important to take coordinated action across the sector and move to net-zero carbon standards through immediate action to raise awareness, implement innovation, and improve carbon management and reporting processes. Tools supporting the reduction of the adverse impacts of construction activities include artificial intelligence tools. The construction industry has long been considered a conservative and traditional industry but is now experiencing a technological revolution. Gradually, artificial intelligence (AI) principles and tools are beginning to be integrated into the various lifecycle processes of construction projects. This paper analyses the AI tools used to analyse carbon footprinting in the construction sector in terms of selected functionalities. The results of the research will form the basis for the development of a strategic plan for the development of AI within the research activities at the Faculty of Civil Engineering in Košice.</p>\",\"PeriodicalId\":501103,\"journal\":{\"name\":\"Mobile Networks and Applications\",\"volume\":\"115 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-07-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Mobile Networks and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1007/s11036-024-02368-y\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mobile Networks and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s11036-024-02368-y","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The Potential of Using Artificial Intelligence (AI) to Analyse the Impact of Construction Industry on the Carbon Footprint
Construction is an important sector of human activity that significantly impacts the environment. The impact of this sector can be analysed from different perspectives, such as consumption of natural resources, waste generation, energy intensity, and environmental change. The sector is increasingly promoting using renewable materials, energy-efficient practices, and planning those respects ecological processes and biodiversity. Against this background, it is important to take coordinated action across the sector and move to net-zero carbon standards through immediate action to raise awareness, implement innovation, and improve carbon management and reporting processes. Tools supporting the reduction of the adverse impacts of construction activities include artificial intelligence tools. The construction industry has long been considered a conservative and traditional industry but is now experiencing a technological revolution. Gradually, artificial intelligence (AI) principles and tools are beginning to be integrated into the various lifecycle processes of construction projects. This paper analyses the AI tools used to analyse carbon footprinting in the construction sector in terms of selected functionalities. The results of the research will form the basis for the development of a strategic plan for the development of AI within the research activities at the Faculty of Civil Engineering in Košice.