Abstract
In the era of big data and artificial intelligence, public datasets are becoming increasingly important for researchers to build and evaluate their models. This paper presents the FIKWaste dataset, which contains time series data for the volume of waste produced in three restaurant kitchens in Portugal. Organic (undifferentiated) and inorganic (glass, paper, and plastic) waste bins were monitored for a consecutive period of four weeks. In addition to the time series measurements, the FIKWaste dataset contains labels for waste disposal events, i.e., when the waste bins are emptied, and technical and non-technical details of the monitored kitchens.
Highlights
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In contrast to other smart city application domains that have seen considerable research in waste management (e.g., [1,2,3,4,5,6,7,8,9]), very little attention has been devoted to the operation of Industrial Kitchens (IKs) (e.g., [10,11])
One of the main goals of the Future Industrial Kitchen (FIK) project was to understand the interactions between the consumption of electricity and water and the generation of waste in such spaces
Summary
A typical dataset for image based approaches would consist of labeled waste bin images. A typical dataset for distance based approaches would consist of time series measurements of the distances measured by the sensor and the corresponding volume represented. Several research works exist in the field of waste management, to the best of our knowledge, there are not many publicly available datasets. This situation contrasts other fields that have seen enormous efforts to release public datasets in the previous years, e.g., electricity [14] and water [15]. We believe that FIKWaste represents a very good and unique contribution to the waste monitoring and management research field as concerns distance based approaches since this was the methodology used in the FIK project
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