1. Automated Water Tank Filteration System Using LDR Sensor
S.Noorjannah Ibrahim, M.S.Lokman Hakim, A.L.Asnawi and N.A. Malik
Department of Electrical and Computer Engineering,
International Islamic University Malaysia
P.O. Box 10, Kuala Lumpur, Malaysia

2. Presentation outline Introduction Objective Methodology Results
Conclusion
Acknowledgment
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3. Introduction
Water is the most valuable resource in this world. Essential for human existence and well-being.
Scheduled inspections and specific cleaning procedures are required to ensure the cleanliness of water in tanks particularly of high-rise buildings and residential areas.
These maintenance works are risky to the water operator’s personnel and can be costly to consumers.
The cleaning procedures sometimes require chemicals that could also
contribute to the maintenance cost and water wastage during the
cleaning process.
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4. What’s in our water Water Constituent AMMONIA DISSOLVED OXYGEN
NITRATES PH
PHOSPHORUS
SALINITY AND CONDUCTIVITY
TEMPERATURE
TURBIDITY
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5. Source of Water Contaminants
MICROBIAL
CHLORINATED ORGANIC
COPPER AND LEAD
Water Treatment Method
CLARIFICATION
FILTRATION
PH ADJUSTMENT
DISINFECTION
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6. [1] http://kmam.moh.gov.my/public-user/drinking-water-quality-standard.html
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7. Objective Requirements
To development of an automated water tank filtration system
To investigate water turbidity using light dependent resistor (LDR) as the sensing unit.
Requirements
The automated water tank filtration system can be expanded into smart home and IoT application.
The system should be flexible to be integrated with other water sensors for monitoring water quality.
Cheap and easy to handle.
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8. Methodology
WATER TANK
LIQUID
PUMP
sensor
Water Filter
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9. Sensing Turbidity with LDR
Analog to Voltage Equation
Turbidity Value Equation
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10. Sensing System LED PVC pipe PUMP OUT to FILTER MICROCONTROLLER LDR
Water flow
MICROCONTROLLER
LDR

11. Experimental Setup
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12. Results
It shows that the turbidity is proportional to the increment of soil concentration.
The high the concentration of soil in water, high turbidity values were
recorded by the LDR sensor in Fig. 5.
As expected, the turbidity of water decreases as the filtration process in progress as shown in Fig.6.
In this test, the turbidity reading can be considered as the reading of continuous flow water because the water from the filter will be flowed back to the tank and create disturbance in the system. Any disturbance in the water will cause the LDR reading to fluctuate. Therefore, results were averaged LDR values for every 1 minute.
The turbidity readings in Fig.6 show constant value for at least 10 minutes at certain location during filtration before giving sharp drop at the 11, 19 and 37 minutes. This suggests that in continuous flow LDR sensor needs some time to stabilize
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15. Conclusion
In this work, an automated water filtration system was developed using a low-powered microcontroller i.e., Arduino Uno and LDR sensing setup. The system is useful because it allows users to monitor the quality of water (from the turbidity parameter) and monitor the water filtration process.
The system is flexible and can be enhanced with more sensors such as pH and conductivity sensors to realize a comprehensive water monitoring system.
Results show that the turbidity values in non-continuous flow has consistent results and follows the logarithmic trend depicted in [7].
Meanwhile, in continuous flow, the turbidity results show that time for measuring turbidity must not be in short duration because the LDR sensor needs to get the stabilize average reading as there are other factors need to be considered in characterization of turbidity.
[7] Madrid, R. E., et al. "Multichannel bacterial growth analyser by impedance and turbidity." Medical and Biological Engineering and Computing 32.6 (1994):
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16. Thank you …