Real Time Water Quality Analysis Framework using Monitoring and Prediction Mechanisms

AbstractIn this paper, an attempt has been made to develop a statistical model based on Internet of Things (IoT) for water quality analysis of river Krishna using different water quality parameters such as pH, conductivity, dissolved oxygen, temperature, biochemical oxygen demand, total dissolved solids and conductivity. These parameters are very important to assess the water quality of the river. The water quality data were collected from six stations of river Krishna in the state of Karnataka. River Krishna is the fourth largest river in India with approximately 1400 km of length and flows from its origin toward Bay of Bengal. In our study, we have considered only stretch of river Krishna flowing in state of Karnataka, i.e., length of about 483 km. In recent years, the mineral-rich river basin is subjected to rapid industrialization, thus polluting the river basin. The river water is bound to get polluted from various pollutants such as the urban waste water, agricultural waste and industrial waste, thus making it unusable for anthropogenic activities. The traditional manual technique that is under use is a very slow process. It requires staff to collect the water samples from the site and take them to the laboratory and then perform the analysis on various water parameters which is costly and time-consuming process. The timely information about water quality is thus unavailable to the people in the river basin area. This creates a perfect opportunity for swift real-time water quality check through analysis of water samples collected from the river Krishna. IoT is one of the ways with which real-time monitoring of water quality of river Krishna can be done in quick time. In this paper, we have emphasized on IoT-based water quality monitoring by applying the statistical analysis for the data collected from the river Krishna. One-way analysis of variance (ANOVA) and two-way ANOVA were applied for the data collected, and found that one-way ANOVA was more effective in carrying out water quality analysis. The hypotheses that are drawn using ANOVA were used for water quality analysis. Further, these analyses can be used to train the IoT system so that it can take the decision whenever there is abnormal change in the reading of any of the water quality parameters.

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Modular AUV System with Integrated Real-Time Water Quality Analysis

Sensors ◽

10.3390/s18061837 ◽

2018 ◽

Vol 18 (6) ◽

pp. 1837 ◽

Cited By ~ 16

Author(s):

Mike Eichhorn ◽

Christoph Ament ◽

Marco Jacobi ◽

Torsten Pfuetzenreuter ◽

Divas Karimanzira ◽

...

Keyword(s):

Water Quality ◽

Real Time ◽

Quality Analysis ◽

Water Quality Analysis

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River water-quality analysis: “critical contaminate detection”, “classification of multiple-water-quality-parameters values” and “real-time notification” by rspa processes

2015 International Electronics Symposium (IES) ◽

10.1109/elecsym.2015.7380842 ◽

2015 ◽

Cited By ~ 1

Author(s):

Chalisa Veesommai ◽

Yasushi Kiyoki

Keyword(s):

Water Quality ◽

Real Time ◽

River Water ◽

Quality Parameters ◽

River Water Quality ◽

Water Quality Parameters ◽

Quality Analysis ◽

Water Quality Analysis

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Hydrological Studies and Water Quality Analysis Around The Limestone Mining in the Hial Area of Bolangir District ,Odisha for The Optimal Use And Sustainable Management of Available Water Resources

International Journal of Contemporary Research and Review ◽

10.15520/ijcrr/2017/8/07/271 ◽

2017 ◽

Vol 08 (07) ◽

Author(s):

S.R. Barick ◽

◽

B.K. Ratha

Keyword(s):

Water Quality ◽

Water Resources ◽

Sustainable Management ◽

Quality Analysis ◽

Water Quality Analysis ◽

Available Water

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STUDI PERBANDINGAN KUALITAS AIR BERSIH DALAM KAITANYA DENGAN AKTIVITAS MASYARAKAT DI SEKITAR SUMBER AIR PADA DESA WAINITU, BATUMERAH, AMAHUSU, DAN HALONG

JURNAL BUDIDAYA PERTANIAN ◽

10.30598/jbdp.2017.13.2.111 ◽

2017 ◽

Vol 13 (2) ◽

pp. 111-119

Author(s):

Lela Uyara ◽

Pieter Kunu ◽

Silwanus M Talakua

Keyword(s):

Water Quality ◽

Quality Standard ◽

Total Coliform ◽

Quality Analysis ◽

Clean Water ◽

Water Quality Analysis ◽

E Coli ◽

Microbiological Parameters ◽

Standard Quality

The study aims to determine the quality of clean water in the villages of Wainitu, Batumerah, Amahusu and Halong by comparing the result of water quality analysis with water quality standard. Water quality analysis includes Physiscal, Chemical, and Microbiological parameters. This research uses descriptive method, this method describes systematics, accurate about facts and characteristic of the quality of clean water of each research location. The results showed that the source of clean water in the village of Batumerah did not meet the standard of clean water quality standards indicated by the number of E. coli and the high total coliform. Keywords: standard quality of clean water, water quality, Wainitu, Batumerah, Amahusu and Halong villages ABSTRAK Penelitian yang bertujuan untuk menetapkan kualitas air bersih di Desa Wainitu, Batumerah, Amahusu dan Halong, dengan membandingkan hasil analisis kualitas air dengan standar baku mutu air bersih. Analisis kualitas air meliputi parameter fisika, kimia dan mikrobiologi. Penelitian ini menggunakan metode deskriptif; metode ini menggambarkan sicara sistematis, akurat, fakta dan karakteristik mengenai kualitas air bersih di masing-masing lokasi penelitian. Hasil penelitian menunjukkan bahwa sumber air bersih di Desa Batumerah tidak memenuhi standar baku mutu air bersih yang ditunjukkan oleh jumlah E. coli dan total Koliform yang tinggi. Kata Kunci: baku mutu air bersih, Desa Wainitu, Batumerah, Amahusu dan Halong, kualitas air

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