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Classification of different types of metal from recyclable household waste for automatic waste separation system Siti Hajar Yusoff; Sazali Mahat; Nur Shahida Midi; Sarah Yasmin Mohamad; Syasya Azra Zaini
Bulletin of Electrical Engineering and Informatics Vol 8, No 2: June 2019
Publisher : Institute of Advanced Engineering and Science

Nowadays, solid waste has become a major problem in Malaysia. However, most people in Malaysia are not aware and take this problem for granted. The rising number of population and massive development in recent years indirectly generated an enormous value of household waste, making the household waste the main generator for solid waste in Malaysia. It stated that only 5 percent of an average 30,000 tons of waste have been recycled in Malaysia. The purpose of the paper is to design a system to separate the metal recyclable household waste automatically and record the data waste collected. There are total of four detectors used to separate the non-metal, steel, copper and aluminum metal waste. The average time used to complete metal separation process by using the proposed prototype is 14.5 seconds. This paper includes a mechanical part, programming part, an electronic design and also the data collected from this proposed system. The system will be programmed using Arduino Mega as a microcontroller to control all the electronic component in the system.

Classification of different types of metal from recyclable household waste for automatic waste separation system Siti Hajar Yusoff; Sazali Mahat; Nur Shahida Midi; Sarah Yasmin Mohamad; Syasya Azra Zaini
Bulletin of Electrical Engineering and Informatics Vol 8, No 2: June 2019
Publisher : Institute of Advanced Engineering and Science

Nowadays, solid waste has become a major problem in Malaysia. However, most people in Malaysia are not aware and take this problem for granted. The rising number of population and massive development in recent years indirectly generated an enormous value of household waste, making the household waste the main generator for solid waste in Malaysia. It stated that only 5 percent of an average 30,000 tons of waste have been recycled in Malaysia. The purpose of the paper is to design a system to separate the metal recyclable household waste automatically and record the data waste collected. There are total of four detectors used to separate the non-metal, steel, copper and aluminum metal waste. The average time used to complete metal separation process by using the proposed prototype is 14.5 seconds. This paper includes a mechanical part, programming part, an electronic design and also the data collected from this proposed system. The system will be programmed using Arduino Mega as a microcontroller to control all the electronic component in the system.

Classification of different types of metal from recyclable household waste for automatic waste separation system Siti Hajar Yusoff; Sazali Mahat; Nur Shahida Midi; Sarah Yasmin Mohamad; Syasya Azra Zaini
Bulletin of Electrical Engineering and Informatics Vol 8, No 2: June 2019
Publisher : Institute of Advanced Engineering and Science

Nowadays, solid waste has become a major problem in Malaysia. However, most people in Malaysia are not aware and take this problem for granted. The rising number of population and massive development in recent years indirectly generated an enormous value of household waste, making the household waste the main generator for solid waste in Malaysia. It stated that only 5 percent of an average 30,000 tons of waste have been recycled in Malaysia. The purpose of the paper is to design a system to separate the metal recyclable household waste automatically and record the data waste collected. There are total of four detectors used to separate the non-metal, steel, copper and aluminum metal waste. The average time used to complete metal separation process by using the proposed prototype is 14.5 seconds. This paper includes a mechanical part, programming part, an electronic design and also the data collected from this proposed system. The system will be programmed using Arduino Mega as a microcontroller to control all the electronic component in the system.

Neural Network Prediction for Efficient Waste Management in Malaysia Siti Hajar Yusoff; Ummi Nur Kamilah Abdullah Din; Hasmah Mansor; Nur Shahida Midi; Syasya Azra Zaini
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 2: November 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i2.pp738-747

Maintaining current municipal solid waste management (MSWM) for the next ten years would not be efficient anymore as it has brought many environmental issues such as air pollution. This project has proposed Artificial Neural Network (ANN) based prediction algorithm that can forecast Solid Waste Generation (SWG) based on population growth factor. This study uses Malaysian population as sample size and the data for weight is acquired via authorized Malaysia statistics’ websites. All data will be normalized in the pre-processing stage before proceeding to the prediction using Visual Gene Developer. This project evaluated the performance using R2 value. Two hidden layers with ten and five nodes were used respectively. The result portrayed that there will be an increase of 29.03 percent of SWG in year 2031 compared to 2012. The limitation to this study is that the data was not based on real time as it was restricted by the government.

Design of Smart Waste Bin and Prediction Algorithm for Waste Management in Household Area Siti Hajar Yusoff; Ummi Nur Kamilah Abdullah Din; Hasmah Mansor; Nur Shahida Midi; Syasya Azra Zaini
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 2: November 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i2.pp748-758

Maintaining current municipal solid waste management (MSWM) for the next ten years would not be efficient anymore as it has brought many environmental issues such as air pollution. This project has proposed Artificial Neural Network (ANN) based prediction algorithm that can forecast Solid Waste Generation (SWG) based on household size factor. Kulliyyah of Engineering (KOE) in International Islamic University Malaysia (IIUM) has been chosen as the sample size for household size factor. A smart waste bin has been developed that can measure the weight, detect the emptiness level of the waste bin, stores information and have direct communication between waste bin and collector crews. This study uses the information obtained from the smart waste bin for the waste weight while the sample size of KOE has been obtained through KOE’s department. All data will be normalized in the pre-processing stage before proceeding to the prediction using Visual Gene Developer. This project evaluated the performance using R2 value. Two hidden layers with five and ten nodes were used respectively. The result portrayed that the average rate of increment of waste weight is 2.05 percent from week one until week twenty. The limitation to this study is that the amount of smart waste bin should be replicated more so that all data for waste weight is directly collected from the smart waste bin.

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