Automated classification of rubber seed clones using combination two different sensors with Arduino / Azanul Amri Mohamad Azmi

Mohamad Azmi, Azanul Amri (2014) Automated classification of rubber seed clones using combination two different sensors with Arduino / Azanul Amri Mohamad Azmi. Degree thesis, Universiti Teknologi MARA (UiTM).

Abstract

This paper describes work on automated system device that able to identify and different type of rubber seed clones. This paper also describes on rubber seed clones classification. There are five different types of rubber seed clone being taken into this work as a sample which are the RRIM2015, RRIM2002, RRIM2020, RRIM2023, and RRIM2024. 30 samples from each type of rubber seed clones is taken of measurement and make it total into 150 samples using in this work. For data measurement, two type of different sensor is involve which is QRE1113 and LDR. The input reading was taken from detected light that reflected form the rubber seed skin surface and the data being controlled by the Arduino, act as controller to perform the desire output. All reading data been taken and will displayed on LCD display. To perform the data analysis, one – way ANOVA measurement is used to get all the the possible value needed in this project which are mean, median, standard error, minimum value and maximum value. Error plot was constructed from ANOVA analysis in order to observe and identify if there any overlapping occur between the rubber seed clone using in this project.

Metadata

Item Type: Thesis (Degree)
Creators:
Creators
Email / ID Num.
Mohamad Azmi, Azanul Amri
2010349665
Contributors:
Contribution
Name
Email / ID Num.
Thesis advisor
Osman, Fairul Nazmie
UNSPECIFIED
Subjects: T Technology > T Technology (General)
T Technology > TK Electrical engineering. Electronics. Nuclear engineering
Divisions: Universiti Teknologi MARA, Shah Alam > Faculty of Electrical Engineering
Programme: Bachelor of Engineering (Hons.) Electronics
Keywords: Rubber seed clones, QRE1113, LDR, data analysis, ANOVA
Date: January 2014
URI: https://ir.uitm.edu.my/id/eprint/115686
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