A Power Efficient IoT Edge Computing Solution for Cooking Oil Recycling

Gomes, Bruno; Melo, Nilsa; Rodrigues, Rafael Nilson; Costa, Pedro; Carvalho, Célio; Karmali, Karim; Karmali, Salim; Soares, Christophe; Torres, João; Sobral, Pedro; Moreira, Rui S.

doi:10.1007/978-3-030-45691-7_11

Cited by 3 publications

(3 citation statements)

References 7 publications

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“…Moreover, on the subject of used cooking oil collection from restaurants, a powerefficient, edge-computing-enabled solution was proposed in [26,27]. Both works refer to the same project.…”

Section: Related Work On Edge Computing Applied To Smart Waste Manage...mentioning

confidence: 99%

“…Both works refer to the same project. While [26] focused on the development of a power-efficient, context-aware edge device for liquid level monitoring, in [27] the authors targeted the specification of a scalable fog-computing-based approach considering an application layer gateway local to each restaurant. The proposed topology allows for cost-effective edge devices with low energy consumption values.…”

Section: Related Work On Edge Computing Applied To Smart Waste Manage...mentioning

confidence: 99%

“…T awake and T sleep expressed in seconds and T sleep = 86,400 − T awake . Given an electric current consumption of I avg in (mA) and a fully charged battery energy capacity E battery in (mAh), the battery life (T battery ), in hours, can be easily calculated as follows[26]:E battery = I avg T battery ⇔ T battery =…”

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confidence: 99%

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An Efficient Edge Computing-Enabled Network for Used Cooking Oil Collection

Gomes,

Soares,

Torres

et al. 2024

Sensors

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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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“…Moreover, on the subject of used cooking oil collection from restaurants, a powerefficient, edge-computing-enabled solution was proposed in [26,27]. Both works refer to the same project.…”

Section: Related Work On Edge Computing Applied To Smart Waste Manage...mentioning

confidence: 99%

Section: Related Work On Edge Computing Applied To Smart Waste Manage...mentioning

confidence: 99%