Automatic Waste Sorter Machine using Proximity Sensor

Vivi Tri Widyaningrum, Ahmad Sahru Romadhon and Rahmawati Safitri

Mechatronics Engineering Department, University of Trunojoyo Madura, Bangkalan, Indonesia

Keywords: Capacitive Proximity Sensor; Inductive Proximity Sensor; Microcontroller; PIR Sensor; Ultrasonic Sensor,

Waste Sorter Machine

Abstract: The waste problem is not a new thing anymore in Indonesia. Public awareness is still lacking not to litter. One

solution that can be done is to make a special trash bin so that it is easy when sorting out which the waste can

be disposed of at a landfill or to be recycled. Therefore, in this study an automatic waste sorter machine was

made. This machine can sort metal trash, plastic bottles, or not both, which are sorted the waste will be put in

different bins according to type. In this machine, Arduino Mega 2560 is used as the main brain, which will

work according to the input obtained from PIR sensor, LDR sensor, inductive proximity sensor, capacitive

proximity sensor, and ultrasonic sensor. Testing on automatic waste sorter machine is carried out using five

types of waste, namely cans, non-transparent plastic bottles that contain water, transparent plastic bottles,

transparent plastic, and report books. From the test results obtained that the automatic waste sorter machine

can detect waste entering the trash can according to its type by 72%. Whereas 28% experienced a detection

error, which was the biggest error occurred in the detection of transparent empty plastic bottles.

1 INTRODUCTION

The problem of waste is not new anymore, especially

in Indonesia. Waste has become a severe problem.

Lack of awareness from the community is one of the

causes. Many people still litter, for example, in

sewers, rivers or the sea. According to a survey

conducted by BPS in 2018 there were 72% of the

public not yet concerned about waste management,

even 81% of plastic waste is dumped into the sea so

that it will be very dangerous to the sustainability of

the oceans (García Nieto et al., 2018). In 2025 it is

predicted that plastic waste entering the sea will

increase, if there is no improvement in waste

management (Jambeck et al., 2015). One solution that

can be done is to make a special trash bin so that it is

easy when sorting out which rubbish can be disposed

of in landfills or which will be recycled.

In some studies a smart trash bin has been created

which can provide information if the trash bin is full

(Fadel, 2017), (Zavare et al., 2017), (Navghane,

Killedar and Rohokale, 2016), but sorting has not

been done for the type of waste included. Subsequent

research has made waste sorting machines, but on

machines made using conveyors (Wath and Ughade,

2019), (Jude et al., 2019), (Chaithanya et al., 2017),

(Samreen et al., 2017), (Williams and Bentil, 2016),

(Ranjitha et al., 2018), (Engineering, 2019), (Chahine

and Ghazal, 2017). This is certainly not suitable for a

small-scale trash bins because to make or buy it

requires expensive costs. Therefore, in this study, an

automatic waste sorter machine designed for a small-

scale was created. This machine uses an inductive

proximity sensor to detect metal waste and a

capacitive proximity sensor to detect plastic bottle

waste. These sensors were chosen because they have

been proven to be able to sort out different types of

waste (Chahine and Ghazal, 2017), (Pushpa et al.,

2015), (C, Badami and H, 2017). Then this machine

is equipped with a PIR sensor to detect whether or not

people are going to throw waste, thus making opening

and closing the trash cans automatically. In addition,

there are also a LDR sensors and an ultrasonic sensors

as additional detectors so that bins become smart

(Mapari et al., 2020). The LDR sensor is used to

detect whether the waste has entered to the trash can

and the ultrasonic sensor is used as a warning when

the trash can is full.

264

Widyaningrum, V., Romadhon, A. and Saﬁtri, R.

Automatic Waste Sorter Machine using Proximity Sensor.

DOI: 10.5220/0010331102640270

In Proceedings of the International Conference on Health Informatics, Medical, Biological Engineering, and Pharmaceutical (HIMBEP 2020), pages 264-270

ISBN: 978-989-758-500-5

2 METHOD

2.1 System Description

The tool made is an automatic waste sorter machine.

In this machine, uses the Arduino Mega 2560

microcontroller as the main brain. The shape of the

Arduino Mega 2560 microcontroller is as shown in

Figure 1. This board has relatively many input/output

pins, namely 54 digital input/output pins of which 15

pins can be used as Pulse Width Modulation (PWM)

outputs, 16 pins as analog inputs, 4 pins as UART

(hardware serial port), 16 MHz crystal oscillator,

USB connection, jack power, header ICSP, and reset

button. Of course this makes it easier for us to make

tools.

Figure 1: The Arduino Mega 2560 Microcontroller.

In an automatic waste sorter machine, arduino will

work based on input obtained from Passive Infrared

Sensor (PIR) sensor, Light-Dependent Resistor

(LDR) sensor, inductive proximity sensor, capacitive

proximity sensor, and ultrasonic sensors. Then as the

output on this machine used a servo motor and

buzzer. The servo motor functions to push or rotate

the trash can cover with a high degree of precision in

terms of angle position, acceleration, and speed.

While the buzzer functions as a warning sound when

the trash can is full. The block diagram of this

automatic waste sorter machine is shown in Figure 2.

The PIR sensor is a sensor that can detect

movement, has a small size, requires small power,

and is quite easy to use, so it is suitable for use on

small-scale machine, such as this automatic waste

sorter machine. The shape of the PIR sensor is as

shown in Figure 3. In this machine, the PIR sensor

functions to detect whether someone is going to take

out the trash or not.

Figure 2: The block diagram of an automatic waste sorter

machine.

Figure 3: The PIR sensor.

The LDR sensor is a resistor component whose

resistance value will vary according to the intensity

of light hitting this sensor. The more light hitting the

LDR sensor, the resistance value will decrease.

Conversely, the less light hitting the LDR sensor, the

greater the resistance value so that it will inhibit the

electric current flowing. The shape of the LDR sensor

is as shown in Figure 4. In an automatic waste sorter

machine, the LDR sensor functions as a detector to

detect whether trash has been put in the trash can or

not.

Figure 4: The LDR sensor.

The proximity sensor is a sensor that is able to

detect objects that are close to within the detection

limit of the sensor even without touching. This sensor

detects the presence of objects using electromagnetic

fields or electromagnetic radiation rays to determine

whether there are certain objects around them. There

are several types of proximity sensors, which in this

automatic waste sorter machine uses an inductive

Automatic Waste Sorter Machine using Proximity Sensor

265

proximity sensor a capacitive proximity sensor. The

inductive proximity sensor functions as a detector

whether the incoming waste is metal waste or not.

The shape of the inductive proximity sensor is shown

in Figure 5. While the capacitive proximity sensor

functions as a detector for incoming waste in the form

of plastic bottles or not. The shape of the capacitive

proximity sensor is shown in Figure 6.

Figure 5: The inductive proximity sensor.

Figure 6: The capacitive proximity sensor.

The ultrasonic sensor is a distance sensor that is

able to read a distance of approximately 2 cm to 4

meters. The ultrasonic sensors work by emitting

ultrasonic waves, which are waves used to detect the

presence of an object by estimating the distance

between the sensor and the object. The shape of the

ultrasonic sensor is shown in Figure 7. In an

automatic waste sorter machine, the ultrasonic sensor

detects whether the trash can is full or not.

Figure 7: The ultrasonic sensor.

2.2 Automatic Waste Sorter Machine

Design

The PIR sensor is placed in the top position of the lid

of the outside of the trash that serves to detect whether

there is movement or not on top of the trash, which in

this case if there is movement means someone will

dispose of waste. The LDR sensor is placed on the lid

of the first inner bin, which serves as a detector

whether or not waste is put in the bin. Then in this

tool used two types of proximity sensors, namely

inductive proximity sensors and capacitive proximity

sensors. The inductive proximity sensor is placed on

the lid of the first inner bin, which is adjacent to the

LDR sensor, which functions as a detector for

incoming waste in the form of metal waste or not.

Whereas the capacitive proximity sensor is placed on

the lid of the second inner bin, which serves as a

detector for incoming waste in the form of plastic

bottles or not. Then as a complement to this machine

there is also an ultrasonic sensor as a detector when

the trash bin is full. Because this machine uses three

bins, there are also three ultrasonic sensors.

The workings of the automatic waste sorter

machine made can be seen in Figure 8, which starts

with a PIR sensor that detects whether there is

movement or not on the trash bin. If a movement is

detected above the trash can, it means that someone

will throw the trash, so the servo motor 1 will rotate

170°. In this case, it means that the outer lid of the

trash can will open automatically so that waste can be

put into the trash. Then on the inside of the trash bin

there are two more lids on the trash bin, which will

also work automatically based on the input it receives.

In an automatic wate sorter machine, when waste

enters the trash, the process is that the incoming waste

is first collected in the lid of the first inner trash can.

On the lid of the first inner trash bin there is an LDR

sensor equipped with an Light-Emitting Diode (LED)

so that the reading is more accurate, which is the

process if there is waste in this lid then the LDR will

read the dark. In this case, it means that garbage has

been detected that has entered the trash and the waste

sorting process wil be carried out.

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266

Figure 8: Automatic waste sorter machine flowchart.

The flowchart of the waste sorting process can be

seen in Figure 9. The process begins with an inductive

proximity sensor that will work to detect waste

entering the lid of the first inner trash bin whether

metal or not. The inductive proximity sensor is placed

on the lid of the first inner trash can, which is next to

the LDR sensor. The process is if the inductive

proximity sensor detects metal waste, the servo motor

2 which is also on the lid of the first inner trash bin

can will rotate 0° so that the metal waste will enter the

metal trash can. However, if the inductive proximity

sensor detects it is not metal waste, the servo motor 2

which is on the lid of the first inner trash bin will

rotate 90° so that the waste will enter the lid of the

second inner trash bin.

Figure 9: The flowchart of the waste sorting process.

On the lid of the second inner trash bin, there is a

capacitive proximity sensor that detects incoming

waste in the form of plastic bottles or not. If the

capacitive proximity sensor detects plastic bottle bins,

servo motor 3 which is on the lid of the second inner

trash bin will rotate 0° so that the plastic bottle bins

will enter the plastic bottle trash bin. However, if the

capacitive proximity sensor detects that it is not

plastic bottle bins, servo motor 3 which is on the lid

Start

The object is near the trash

The PIR sensor detects

the movement of objects

Servo 1 rotates 170°

LDR sensor detects dark

Waste Sortin

Process

Garbage enters the

appropriate type

End

Yes

There is

movement?

Dark?

Start

Waste

Inductive proximity

sensor detects waste

Servo 2 rotates 90°

Servo 2 rotates

Capacitive proximity

sensor detects waste

Servo 3 rotates

Buzzer

Metal

Ultrasonic

sensor 1 detects

metal bins

Ultrasonic sensor 3

detect non-metal and

ast

Ultrasonic

sensor 2 detects

plastic bottle

Plastic

Full

Automatic Waste Sorter Machine using Proximity Sensor

267

of the second inner trash bin, will rotate 110° so that

the waste will enter the non-metal and not plastic

bottles trash bin. After the waste enters the

appropriate type of waste, then the ultrasonic sensor

will detect whether the trash bin is full or not. In this

machine three trash bins are used so that there are also

three ultrasonic sensors, namely ultrasonic sensor 1

placed in metal bins, ultrasonic sensor 2 placed in

plastic bottle bins, and ultrasonic sensor 3 placed in

non-metal and also not a plastic bottle bins. If any of

the three ultrasonic sensors detect that the trash bin is

full, the buzzer will sound as a warning sign.

3 RESULTS AND DISCUSSIONS

The results of making an automatic waste sorter

machine are shown in Figure 10. The description of

the numbering in the image is :

1. Tool wall

2. Power supply 12V 5A

3. Cover the second inner bin

4. Tool framework

5. Trash that is neither metal nor plastic bottle

6. Cover the first inner bin

7. Arduino Mega 2560

8. Metal trash can

9. Plastic bottle trash can

In Figure 10, the lid of the trash can number 6 is the

place for the LDR sensor, inductive proximity sensor,

and also the servo motor 2. Then for the placement of

the PIR sensor, servo motor 1, and buzzer is the top

position on the outer trash can cover, which is located

just above number 6. While the lid of the trash bin

number 3 is the place for the capacitive proximity

sensor and the servo motor 3.

Figure 10: The results of making an automatic waste sorter

machine.

Experiments on the automatic waste sorter

machine were carried out using five types of waste,

namely cans, non-transparent plastic bottles filled

with water, transparent empty plastic bottles, plastic,

and report books. Each type of waste was tested ten

times, the results are shown in Table 1, Table 2, Table

3, Table 4, and Table 5.

The results of automatic waste sorter machine

testing using cans waste are shown in Table 1. At ten

times the experiment carried out trash can be

announced as metal waste. This shows that the

detection has been done 100% correct.

Table 1: Automatic waste sorter machine testing results for

cans waste.

Trial to-

Cans included in the category

Metal Plastic Not Both

√

- -

√

- -

√

- -

√

- -

√

- -

√

- -

√

- -

√

- -

√

- -

√

- -

Percenta

e 100% 0% 0%

In Table 2 is the result of testing the automatic

waste sorter machine using the waste of non-

transparent plastic bottles filled with water. In ten

experiments that have been carried out the waste of

non-transparent plastic bottles filled with water were

detected as plastic waste. This of course also shows

that the detection has been done is 100% correct.

Table 2: Automatic waste sorter machine testing results for

the waste of non-transparent plastic bottles filled with

water.

Trial to-

The waste of non-transparent plastic

bottles filled with water included in the

category

Metal Plastic Not Both

√

10 -

√

Percenta

e 0% 100% 0%

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268

In Table 3 is the result of testing the automatic

waste sorter machine using transparent empty plastic

bottles bins. In ten experiments that have been carried

out, transparent empty plastic bottles are detected as

non-metal and non-plastic waste (not both). This

certainly shows that the detection that has been done

is 100% wrong, because empty plastic bottles that are

transparent should be included in the type of plastic

waste.

Table 3: Automatic waste sorter machine testing results for

transparent empty plastic bottles.

Trial to-

Transparent empty plastic bottles

included in the category

Metal Plastic Not Both

1 - -

√

2 - -

√

3 - -

√

4 - -

√

5 - -

√

6 - -

√

7 - -

√

8 - -

√

9 - -

√

10 - -

√

Percenta

e 0% 0% 100%

In Table 4 is the result of testing the automatic

waste sorter machine using plastic waste. In ten

experiments carried out plastic waste was detected as

non-metal and non-plastic waste (not both). This

shows that the detection has been done 100% correct.

Table 4: Automatic waste sorter machine testing results for

plastic waste.

Trial to-

Plastic included in the category

Metal Plastic Not Both

1 - -

√

2 - -

√

3 - -

√

4 - -

√

5 - -

√

6 - -

√

7 - -

√

8 - -

√

9 - -

√

10 - -

√

Percentage 0% 0% 100%

In Table 5 is the result of testing automatic waste

sorter machine using the report book waste. In the ten

experiments that have been carried out, the report

book waste is twice detected as plastic waste and

three times it is detected as non-metal and non-plastic

waste. This shows that the detection has been done is

only 60% correct, while the 40% experienced an error

because the report book waste is detected as plastic.

Table 5: Automatic waste sorter machine testing results for

report book waste.

Trial to-

Report book included in the category

Metal Plastic Not Both

√

2--

√

3--

√

4--

√

- √ -

- - √

- √ -

- - √

Percentage 0% 40% 60%

4 CONCLUSIONS

From the test results, it can be concluded that 72% the

automatic waste sorter machine can detect waste

entering the trash according to its type. Then the

automatic waste sorter machine has a detection error

of 28%. The biggest error occurred in detecting

transparent empty plastic bottles. This is because

capacitive proximity sensors are more sensitive if the

plastic bottles detected are not transparent.

ACKNOWLEDGEMENTS

The author would like to thank the financial support

of DIPA FT UTM 2020 until this article can be

published.

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