Littering is an environmental problem that affects citizens’ economy, safety, and health. Natural and rural areas are often targets of abandoned littering, while urban areas often accumulate more waste than can be disposed of in a timely manner. Minimizing littering and waste is a critical sustainability challenge requiring the cooperation of different professionals and agencies. In this paper, we report our vision and preliminary proposal for a model-driven approach to address the automated localization and identification of abandoned waste. Our solution envisages the usage of digital process twins to enable the specification of cost-effective and self-adaptive procedures fed by data crowdsourced from the real world.
Di Salle, A., Fedeli, A., Iovino, L., Mariani, L., Micucci, D., Rebelo, L., et al. (2024). Waste Management Through Digital Twins and Business Process Modeling. In MODELS Companion '24: Proceedings of the ACM/IEEE 27th International Conference on Model Driven Engineering Languages and Systems (pp.513-517). Association for Computing Machinery, Inc [10.1145/3652620.3687796].
Waste Management Through Digital Twins and Business Process Modeling
Mariani L.;Micucci D.;Rossi M. T.
2024
Abstract
Littering is an environmental problem that affects citizens’ economy, safety, and health. Natural and rural areas are often targets of abandoned littering, while urban areas often accumulate more waste than can be disposed of in a timely manner. Minimizing littering and waste is a critical sustainability challenge requiring the cooperation of different professionals and agencies. In this paper, we report our vision and preliminary proposal for a model-driven approach to address the automated localization and identification of abandoned waste. Our solution envisages the usage of digital process twins to enable the specification of cost-effective and self-adaptive procedures fed by data crowdsourced from the real world.
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