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An Efficient Edge Computing-Enabled Network for Used Cooking Oil Collection.
Gomes, Bruno; Soares, Christophe; Torres, José Manuel; Karmali, Karim; Karmali, Salim; Moreira, Rui S; Sobral, Pedro.
Afiliación
  • Gomes B; Faculty of Science and Technology, University Fernando Pessoa, 4249-004 Porto, Portugal.
  • Soares C; Hardlevel-Renewable Energies, 4410-235 Vila Nova de Gaia, Portugal.
  • Torres JM; Faculty of Science and Technology, University Fernando Pessoa, 4249-004 Porto, Portugal.
  • Karmali K; LIACC-Artificial Intelligence and Computer Science Laboratory, University of Porto, 4200-465 Porto, Portugal.
  • Karmali S; Faculty of Science and Technology, University Fernando Pessoa, 4249-004 Porto, Portugal.
  • Moreira RS; LIACC-Artificial Intelligence and Computer Science Laboratory, University of Porto, 4200-465 Porto, Portugal.
  • Sobral P; Hardlevel-Renewable Energies, 4410-235 Vila Nova de Gaia, Portugal.
Sensors (Basel) ; 24(7)2024 Mar 31.
Article en En | MEDLINE | ID: mdl-38610447
ABSTRACT
In Portugal, more than 98% of domestic cooking oil is disposed of improperly every day. This avoids recycling/reconverting into another energy. Is also may become a potential harmful contaminant of soil and water. Driven by the utility of recycled cooking oil, and leveraging the exponential growth of ubiquitous computing approaches, we propose an IoT smart solution for domestic used cooking oil (UCO) collection bins. We call this approach SWAN, which stands for Smart Waste Accumulation Network. It is deployed and evaluated in Portugal. It consists of a countrywide network of collection bin units, available in public areas. Two metrics are considered to evaluate the system's success (i) user engagement, and (ii) used cooking oil collection efficiency. The presented system should (i) perform under scenarios of temporary communication network failures, and (ii) be scalable to accommodate an ever-growing number of installed collection units. Thus, we choose a disruptive approach from the traditional cloud computing paradigm. It relies on edge node infrastructure to process, store, and act upon the locally collected data. The communication appears as a delay-tolerant task, i.e., an edge computing solution. We conduct a comparative analysis revealing the benefits of the edge computing enabled collection bin vs. a cloud computing solution. The studied period considers four years of collected data. An exponential increase in the amount of used cooking oil collected is identified, with the developed solution being responsible for surpassing the national collection totals of previous years. During the same period, we also improved the collection process as we were able to more accurately estimate the optimal collection and system's maintenance intervals.
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Texto completo: 1 Bases de datos: MEDLINE Idioma: En Revista: Sensors (Basel) Año: 2024 Tipo del documento: Article País de afiliación: Portugal

Texto completo: 1 Bases de datos: MEDLINE Idioma: En Revista: Sensors (Basel) Año: 2024 Tipo del documento: Article País de afiliación: Portugal