Automated Waste Separated Machine

Low, Xian Min (2017) Automated Waste Separated Machine. Technical Report. UTeM, Melaka. (Submitted)

Text Automated Waste Separated Machine - Low Xian Min - 24 pages.pdf - Submitted Version Download (547kB)

Abstract

Beverage container waste has been brought serious impacts to our environmental. For example, energy consumption of manufacturing drinking containers equivalences to 30 to 50 million barrels of crude oil each year. Besides that, process of making these containers generate large amount of greenhouse gas that causes global warming. Moreover, toxic is emitted to the air and water from the process of turn bauxite into alumina. Undeniable, demand of using drinking container is keep on rising, which cannot be eliminated. Hence, recycle is a method to be used to lower these impacts to the environment by controlling the quantity of drinking container available in our surrounding. Common way to perform recycle activity is using manually picking and sorting drinking bottle into categories but it is hard to solve the problem in long term due to high rate of beverage production and high cost to manage waste generated every day. Thus, machine vision is proposed to solve the problem. Machine vision is one of the popular technique for object detection. The extent of this project is using machine vision to recognise type of waste (Note: Usual shape of drinking bottle) by extracting the colour of waste. Colour value (RGB) is transformed into HSV (Hue, Saturation and Value). Histograms are created for comparison between detected object and saved object in database. Then, sort them into different place by using machine learning. OpenCV library play a crucial role in this project, which is included in Microsoft Visual Studio 2012 with C++ language to write the coding for waste recognition. As a summary, the machine vision colour detection is used to build Automated Waste Separated Machine and able to achieve 80% rate of success of waste detection.

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