OPTIMIZATION THE COAGULATION PROCESS AT WATER TREATMENT PLANTS (WTP) OF REGIONAL DRINKING WATER COMPANIES USING NEURAL NETWORKS AND INTERNET OF THINGS (IOT)
Drinking water can be said to be feasible for consumption if it meets the water quality standards in accordance with the Minister of Health of Republic of Indonesia Regulation No.492/2010 on Requirements for Drinking Water Quality. drinking water is a primary need to support life. Approximately 70...
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| Format: | Theses |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/55531 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | Drinking water can be said to be feasible for consumption if it meets the water
quality standards in accordance with the Minister of Health of Republic of Indonesia Regulation No.492/2010 on Requirements for Drinking Water Quality.
drinking water is a primary need to support life. Approximately 70% of the
availability of drinking water in big cities is supported by the Regional Water
Company (PDAM). Currently, there are still many PDAMs that use manual
methods to monitor the quality of raw water and its processing, so that the
quality of the output is less awake. Raw water is the source of source that
will be processed by PDAM, which then the results of processed in the form
of drinking water will be distributed to drinking water consumers receorded in
PDAM.
In this thesis, is built a system prototype that can measure the quality of
raw water using sensors, and predicts the need for chemicals or coagulants
for water treatment in Water Treatment Plant (WTP) buildings by utilizing
Internet of Things (IoT) communications. The sensor used can measure several water quality parameters including pH to determine the level of acidity
or alkalinity of water, Dissolved Oxygen (DO) to determine dissolved oxygen
levels in water and turbidity to determine levels of turbidity in water. System
processing is carried out by a microcontroller. The Artificial Neural Network
(ANN) method is used to calculate the number of coagulants needed for the
water treatment process, which will be used by consumers. This system can
predict the need for chemicals or coagulants for automatic water treatment
with 3 (three) main parameters, including pH, DO, and turbidity, besides that
the system can also display raw water quality measurement data, coagulant
data, and water pump discharge data by utilizing IoT communication. By
using this system, the use of coagulant materials is more efficient and the quality of treated water does not fall out of the predetermined range of values.
This reduces the possibility for PDAM consumers to use water with quality
beyond standard limits. |
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