scholarly journals TEKNOLOGI PEMANTAUAN KUALITAS AIR ONLINE BERBASIS GSM DENGAN METODE SMS DI SUNGAI KAPUAS

2018 ◽  
Vol 6 (2) ◽  
Author(s):  
Heru Dwi Wahjono
Keyword(s):  
Water Quality ◽  
River Water ◽  
Monitoring System ◽  
Treatment Plant ◽  
Water Treatment Plant ◽  
Water Quality Monitoring ◽  
High Water ◽  
Quality Monitoring ◽  
Raw Water ◽  
The People

Kapuas River is the largest river on the Borneo island and become the source of water for the people of this island. In Pontianak City, Kapuas River is become the source of raw water for the local water company (PDAM). To maintain product quality, PDAM Pontianak always monitor this river water quality. During the dry season or during high water, raw water quality Kapuas river becomes salty. Meanwhile, during the rainy season brings torrential river water from upstream mud and water turned into peat. To monitor water quality changes in the Kapuas river in the intake location, PDAM Pontianak has installed an online and real time water quality monitoring system using GSM technology. This paper discusses the installation process online water quality monitoring system starting from the preparation, determination of the location until the process of testing the system. The results of monitoring by the monitoring system is expected to assist the production department to determine the necessary action if there is a change of quality of raw water Kapuas river. Keywords: GSM Communication Based Online Monitoring System, Telemetry System, Intake PDAM Pontianak, Multi Probe Digital Sensor, Water Treatment Plant

scholarly journals PEMANTAUAN KUALITAS AIR ONLINE DAN REALTIME DI INTAKE PDAM TAMAN KOTA CENGKARENG DRAIN DKI JAKARTA

2018 ◽  
Vol 5 (2) ◽  
Author(s):  
Heru Dwi Wahjono
Keyword(s):  
Water Quality ◽  
Water Treatment ◽  
Water Supply ◽  
Treatment Plant ◽  
Water Treatment Plant ◽  
Water Quality Monitoring ◽  
Quality Monitoring ◽  
Clean Water ◽  
Raw Water

The need for clean water in big cities is very dependent on water supply by water companies (PDAM). The increasing demand for clean water in big cities is proportional to the increasing of number population and industry, but not comparable to the clean water supply and quality of raw water available. PDAM has made various efforts to improve the quality of clean water services to the community. One of the effort is to improve the performance of water treatment plant (WTP). To support the improvement of the performance of WTP, required water quality monitoring at the intake location in use. This paper discusses the online and realtime water quality monitoring at the water intake location using a multi-probe digital sensor and GSM technology. This observation data is used as a comparative data analysis of laboratory data on raw water source PDAM Taman Kota (Cengkareng Drain). Keywords: air baku air minum, intake PDAM Taman Kota Cengkareng Drain, pemantuan kualitas air, multi probe digital sensor, teknologi online monitoring, Water Treatment Plant

Study on Prediction Model of Dissolved Oxygen about Water Quality Monitoring System Based on BP Neural Network

2014 ◽  
Vol 912-914 ◽  
pp. 1407-1411 ◽  
Author(s):  
Jing Xin Yan ◽  
Li Juan Yu ◽  
Wen Wu Mao ◽  
Shou Qi Cao
Keyword(s):  
Neural Network ◽  
Water Quality ◽  
Dissolved Oxygen ◽  
Prediction Model ◽  
Monitoring System ◽  
Bp Neural Network ◽  
Water Quality Monitoring ◽  
High Water ◽  
Eriocheir Sinensis ◽  
Quality Monitoring

Eriocheir sinensis should cultivate in high water quality ponds, which is affected by many combined factors such as physics, chemistry, biology etc. Using the real-time water quality monitoring historical data to test one of the water quality indexes and predict this index in the next time has great significance. The dissolved oxygen is one of the most important indexes in aquaculture, such as in the Eriocheir sinensis pond. This paper established a dissolved oxygen prediction model of water quality monitoring system based on BP neural network. The forecast data which is predicted by the established model could fit the actual monitoring data very well.

Analisis Kelembagaan dalam Monitoring Kualitas Air Sungai Ciliwung di Wilayah Provinsi DKI Jakarta

2018 ◽  
Vol 20 (2) ◽  
pp. 89
Author(s):  
Aflakhur Ridlo
Keyword(s):  
Water Quality ◽  
River Water ◽  
Monitoring System ◽  
Water Quality Monitoring ◽  
River Water Quality ◽  
Quality Monitoring ◽  
Administrative Authority ◽  
Public Intervention ◽  
Communication And Coordination ◽  
Water Quality Problem

Institutional research and policy analysis of water quality monitoring of the Ciliwung River has been conducted since the year 2015. This activity is the result of cooperation between the Ministry of Environment and Forestry of Indonesia and the Agency for Assessment and Application of Technology. Due to the complexity of the Ciliwung River flows and water quality problem that passed the administrative authority of DKI Jakarta, the methodology of this study was emphasized in depth interviews to stakeholders in the management of the Ciliwung River. The plan to install some online system of river water quality monitoring is expected to run well and in accordance with existing laws and regulations. In addition, the readiness of the operationalization of this monitoring system to run well. Institutional strengthening forms and open method of coordination can be adopted to reduce communication and coordination barriers that are rigid and Weberian. From this study it is concluded that Jakarta Environmental Management Agency is the strongest candidate as one of the managers of online monitoring system of Ciliwung river water quality. Institutionally public intervention on river management in general can suppress water quality pollution which can threat n the health of people living around Jakarta area. Online Mortitoring system can be utilized by preparing a reliable institutional arrangements

scholarly journals Spatial Variations of Drinking Water Quality Monitoring in Water Treatment Plant Using Environmetric Techniques

2013 ◽  
pp. 325-329 ◽  
Author(s):  
Manutha Appa Rwoo ◽  
Hafizan Juahir ◽  
Azman Azid ◽  
Sharifah Mohd Sharif ◽  
Nor Malissa Roslan ◽  
...  
Keyword(s):  
Water Quality ◽  
Drinking Water ◽  
Water Treatment ◽  
Treatment Plant ◽  
Water Treatment Plant ◽  
Water Quality Monitoring ◽  
Spatial Variations ◽  
Drinking Water Quality ◽  
Quality Monitoring

The development of water quality monitoring system using internet of things

10.32698/0852 ◽  
2020 ◽  
Vol 3 (1) ◽  
pp. 14
Author(s):  
Sharifah Nurulhuda Tuan Mohd Yasin ◽  
Mohd Fauzi Mohd Yunus ◽  
Nur Bahiyah Abdul Wahab
Keyword(s):  
Water Quality ◽  
River Water ◽  
Monitoring System ◽  
Water Conservation ◽  
Biological Diversity ◽  
Positive Impact ◽  
Water Quality Monitoring ◽  
Quality Monitoring ◽  
The Internet ◽  
Vital Resource

Biological diversity or biodiversity is an important element in the river water management system. The interaction between the various organisms in the river makes it a very complex ecological system. Therefore, water safety issues are a very important issue. Consumer complaints and reports made by the relevant government departments indicate that consumers are dissatisfied with the quality of water supplied. Hence, a concept in which equipment, machines, sensors and devices are connected to the Internet and there is data collection and transfer through the network developed to follow the river water quality index. Integration of the elements of sustainability and IR4.0 through the Internet of Thing by adopting electronic and Internet applications of Thing has a very positive impact to refresh the approach to lesions in Malaysia. The project aims to develop a wireless water quality monitoring system that aids in continuous measurements of water conditions based on pH and turbidity measurements. The developed system was successfully detecting both the pH and turbidity values. Water analysis and monitoring is a very important aspect of water conservation and protection. Water is a vital resource that runs more quickly overtime. To ensure continued supply of safe, clean drinking water, together as community to protect and to this vital resource.

scholarly journals IoT Based Real-time River Water Quality Monitoring System

2019 ◽  
Vol 155 ◽  
pp. 161-168 ◽  
Author(s):  
Mohammad Salah Uddin Chowdury ◽  
Talha Bin Emran ◽  
Subhasish Ghosh ◽  
Abhijit Pathak ◽  
Mohd. Manjur Alam ◽  
...  
Keyword(s):  
Water Quality ◽  
Real Time ◽  
River Water ◽  
Monitoring System ◽  
Water Quality Monitoring ◽  
River Water Quality ◽  
Quality Monitoring

scholarly journals Integration of Remote Sensing and Mexican Water Quality Monitoring System Using an Extreme Learning Machine

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4118
Author(s):  
Leonardo F. Arias-Rodriguez ◽  
Zheng Duan ◽  
José de Jesús Díaz-Torres ◽  
Mónica Basilio Hazas ◽  
Jingshui Huang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Quality ◽  
Extreme Learning Machine ◽  
Monitoring System ◽  
Field Measurements ◽  
Water Quality Monitoring ◽  
Quality Monitoring ◽  
Chl A ◽  
Learning Machine ◽  
Level 2

Remote Sensing, as a driver for water management decisions, needs further integration with monitoring water quality programs, especially in developing countries. Moreover, usage of remote sensing approaches has not been broadly applied in monitoring routines. Therefore, it is necessary to assess the efficacy of available sensors to complement the often limited field measurements from such programs and build models that support monitoring tasks. Here, we integrate field measurements (2013–2019) from the Mexican national water quality monitoring system (RNMCA) with data from Landsat-8 OLI, Sentinel-3 OLCI, and Sentinel-2 MSI to train an extreme learning machine (ELM), a support vector regression (SVR) and a linear regression (LR) for estimating Chlorophyll-a (Chl-a), Turbidity, Total Suspended Matter (TSM) and Secchi Disk Depth (SDD). Additionally, OLCI Level-2 Products for Chl-a and TSM are compared against the RNMCA data. We observed that OLCI Level-2 Products are poorly correlated with the RNMCA data and it is not feasible to rely only on them to support monitoring operations. However, OLCI atmospherically corrected data is useful to develop accurate models using an ELM, particularly for Turbidity (R2=0.7). We conclude that remote sensing is useful to support monitoring systems tasks, and its progressive integration will improve the quality of water quality monitoring programs.

Sign in / Sign up

Export Citation Format

Share Document