Globally, one of the most economically impacting problems in the modern era concerns food waste on the consumer side. In this framework, the here-proposed work stems from the idea of combining the potential of a modern smart home with the need to reduce domestic food waste. For this purpose, the paper proposes a food waste reduction (FWR) architecture composed of a smart sensing network and an actuation system. The sensing network is realized via intelligent sensor nodes able to real-time assess the monitored food shelf life and the storage condition, as well as localize them in the environment. If bad conditions of storage are recognized, the sensor node is able to call for actuation system intervention. This latter system includes a robot platform that can localize food, manipulate it, and guarantee better storage conditions to preserve its shelf life. Experimental tests on 50 operations show that in more than 60% of cases, the automatic operations have been successfully completed starting from the sensor node call for intervention, up to the object manipulation routine to ensure an adequate storage condition of the food. The promising results achieved by the present pilot study pave the way for investigations on a new main goal in the smart homes’ framework, i.e., automatic food waste management.

AI for Food Waste Reduction in Smart Homes / Mezzina, Giovanni; Ciccarese, Dionisio; De Venuto, Daniela. - STAMPA. - 1668:(2023), pp. 87-99. (Intervento presentato al convegno 22nd International Conference on Web Engineering, ICWE 2022 tenutosi a Bari, Italy nel July 5-8 2022) [10.1007/978-3-031-25380-5_7].

AI for Food Waste Reduction in Smart Homes

Giovanni Mezzina
;
Dionisio Ciccarese;Daniela De Venuto
2023-01-01

Abstract

Globally, one of the most economically impacting problems in the modern era concerns food waste on the consumer side. In this framework, the here-proposed work stems from the idea of combining the potential of a modern smart home with the need to reduce domestic food waste. For this purpose, the paper proposes a food waste reduction (FWR) architecture composed of a smart sensing network and an actuation system. The sensing network is realized via intelligent sensor nodes able to real-time assess the monitored food shelf life and the storage condition, as well as localize them in the environment. If bad conditions of storage are recognized, the sensor node is able to call for actuation system intervention. This latter system includes a robot platform that can localize food, manipulate it, and guarantee better storage conditions to preserve its shelf life. Experimental tests on 50 operations show that in more than 60% of cases, the automatic operations have been successfully completed starting from the sensor node call for intervention, up to the object manipulation routine to ensure an adequate storage condition of the food. The promising results achieved by the present pilot study pave the way for investigations on a new main goal in the smart homes’ framework, i.e., automatic food waste management.
2023
22nd International Conference on Web Engineering, ICWE 2022
978-3-031-25379-9
AI for Food Waste Reduction in Smart Homes / Mezzina, Giovanni; Ciccarese, Dionisio; De Venuto, Daniela. - STAMPA. - 1668:(2023), pp. 87-99. (Intervento presentato al convegno 22nd International Conference on Web Engineering, ICWE 2022 tenutosi a Bari, Italy nel July 5-8 2022) [10.1007/978-3-031-25380-5_7].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11589/248794
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