Peer-reviewed articles 17,970 +



Title: THE OPTICAL METHOD FOR THE PLASTIC WASTE RECOGNITION AND SORTING IN A REVERSE VENDING MACHINE

THE OPTICAL METHOD FOR THE PLASTIC WASTE RECOGNITION AND SORTING IN A REVERSE VENDING MACHINE
A. N. Kokoulin;A. A. Yuzhakov;A. I. Tur;A. I. Knyazev
1314-2704
English
19
4.1
Reverse vending machines (RVM) are a key part of used plastic containers utilization system in Europe and the United States. Waste recognition and sorting in RVM machines can be performed by any of the following procedures: by determining the container material (e.g. using the IR-spectrometer), by recognition of the container type by its shape, or by the barcode identification.[1] These three basic control-procedures make any attempt of the fraud completely impossible. But at the same time, it makes the RVM too expensive. With the modern computer vision technologies, we can design another kind of efficient and non-expensive RVM having the same functionality using energy-efficient IoT MCUs. In this paper an efficient approach of computer vision and image processing application in automatic recognition of empty recyclable containers is considered. The RVM construction was optimized to be as small as possible due to binocular optical system and the human-machine interaction of RVM was reduced due two levels of data processing (distributed functionality) making it possible to embed the module of RVM into the vending machine. The list of the available object recognition methods and frameworks was revised because IoT controllers and tiny single-board computers usually have memory and computational restrictions. CNN training takes into account that recycled cans or bottles could be twisted or jammed. Also, we analyze the performance of image recognition procedures in Python and C ++ languages.
conference
19th International Multidisciplinary Scientific GeoConference SGEM 2019
19th International Multidisciplinary Scientific GeoConference SGEM 2019, 30 June - 6 July, 2019
Proceedings Paper
STEF92 Technology
International Multidisciplinary Scientific GeoConference-SGEM
Bulgarian Acad Sci; Acad Sci Czech Republ; Latvian Acad Sci; Polish Acad Sci; Russian Acad Sci; Serbian Acad Sci & Arts; Slovak Acad Sci; Natl Acad Sci Ukraine; Natl Acad Sci Armenia; Sci Council Japan; World Acad Sci; European Acad Sci, Arts & Letters; Ac
793-800
30 June - 6 July, 2019
website
cdrom
5906
reverse vending machine; IoT; neural network; plastic waste