The efficient tracking of Construction and Demolition Wastes (CDWs) is pivotal in a perspective of sustainability and circularity in the construction sector. Sensing and digital technologies can undoubtedly play a relevant role in this context. This paper proposes an innovative approach for detection, quantification, and characterization of CDWs in order to provide information exploitable through optimized valorization routes made available via dedicated service platforms. The preliminary results are promising, and the solution will be iteratively refined and improved thanks to continuous data collection from real-world scenarios

How to Valorize Construction and Demolition Wastes? Beyond the State of the art Through Vision Systems and Artificial Intelligence Tools / Cosoli, G.; Salerno, G.; Calcagni, M. T.; Pandarese, G.; Violini, L.; El Masri, E.; De Melo Ribeiro, H.; Abbas, M. A. A.; Revel, G. M.. - (2024), pp. 552-557. (Intervento presentato al convegno 2024 IEEE International Workshop on Metrology for Living Environment, MetroLivEnv 2024 tenutosi a Chania, Greece nel 12 - 14 June 2024) [10.1109/MetroLivEnv60384.2024.10615834].

How to Valorize Construction and Demolition Wastes? Beyond the State of the art Through Vision Systems and Artificial Intelligence Tools

Cosoli G.
Primo
;
Salerno G.
Secondo
;
Calcagni M. T.;Pandarese G.;Violini L.;Revel G. M.
2024-01-01

Abstract

The efficient tracking of Construction and Demolition Wastes (CDWs) is pivotal in a perspective of sustainability and circularity in the construction sector. Sensing and digital technologies can undoubtedly play a relevant role in this context. This paper proposes an innovative approach for detection, quantification, and characterization of CDWs in order to provide information exploitable through optimized valorization routes made available via dedicated service platforms. The preliminary results are promising, and the solution will be iteratively refined and improved thanks to continuous data collection from real-world scenarios
2024
979-8-3503-8501-4
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11566/341253
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