DSpace logo

Please use this identifier to cite or link to this item: http://142.54.178.187:9060/xmlui/handle/123456789/1263
Full metadata record
DC FieldValueLanguage
dc.contributor.authorAli, Tauha Hussain-
dc.contributor.authorAkhund, Muhammad Akram-
dc.contributor.authorMemon, Nafees Ahmed-
dc.contributor.authorMemon, Aftab Hamed-
dc.contributor.authorImad, Hafiz Usama-
dc.contributor.authorKhahro, Shabir Hussain-
dc.date.accessioned2019-11-14T06:52:39Z-
dc.date.available2019-11-14T06:52:39Z-
dc.date.issued2019-03-02-
dc.identifier.urihttp://142.54.178.187:9060/xmlui/handle/123456789/1263-
dc.description.abstractNowadays, the construction industry faces numerous problems, among which, managing construction and demolition waste are of key concern. As this waste is a threat to the environment and it demands significant financial resources to be tackled. Though human being can think in multi-dimension, but to consider all the contributing attributes for waste management is beyond its limit. For this purpose, there has been always a need of a artificial intelligence (AI) which could help in directing towards the management of the produced waste. Generation of construction and demolition (C&D) waste is unavoidable in any circumstance and handling this waste is always a menace to the managers. This requires high technicalities and a huge amount of resources to be spent on proper waste control. This paper aims to develop a conceptual framework for an effective construction waste management system (EMS) by application of artificial intelligence (AI), which could decide a suitable technique to be implemented on the produced waste. A comprehensive review of waste generation attributes, waste management techniques, and adaptability & feasibility is carried out to identify loopholes and limitations of each technique. The proposed EMS will help the construction practitioners to apply the most suitable, most viable, most feasible and most economical waste management technique to control on-site construction and demolition waste, based on its own capacity and type of waste.en_US
dc.language.isoen_USen_US
dc.publisher8th International Conference on Industrial Technology and Management (ICITM)en_US
dc.subjectEngineering and Technologyen_US
dc.subjectWaste managementen_US
dc.subjectArtificial intelligenceen_US
dc.subjectConstruction industryen_US
dc.subjectProductionen_US
dc.subjectSolidsen_US
dc.subjectSociologyen_US
dc.titleApplication of Artifical Intelligence in Construction Waste Managementen_US
dc.typeProceedingsen_US
Appears in Collections:Proceedings

Files in This Item:
File Description SizeFormat 
8710680.htm115 BHTMLView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.