An IoT and machine learning solutions for monitoring agricultural water quality: a robust framework DOI Creative Commons
Mushtaque Ahmed Rahu, Muhammad Mujtaba Shaikh, Sarang Karim

et al.

Mehran University Research Journal of Engineering and Technology, Journal Year: 2023, Volume and Issue: 43(1), P. 192 - 192

Published: Dec. 30, 2023

All living things, comprising animals, plants, and people require water to survive. The world is covered in water, just 1 percent of it fresh functional. importance value freshwater have increased due population growth rising demands. Approximately more than 70 the world's used for agriculture. Agricultural employees are least productive, inefficient, heavily subsidized users world. They also utilize most overall. Irrigation consumes a considerable amount water. field's supply needs be safeguarded. A critical stage estimating agricultural production crop irrigation. global shortage serious issue, will only get worse years come. Precision agriculture intelligent irrigation solutions that solve aforementioned issues. Smart systems other modern technologies must improve quantity high-quality Such system has potential quite accurate, but requires data about climate quality region where used. This study examines smart using Internet Things (IoT) cloud-based architecture. water's temperature, pH, total dissolved solids (TDS), turbidity all measured by this device before processed cloud range machine learning (ML) approaches. Regarding content limits, farmers given accurate information. Farmers can increase effective techniques. ML methods support vector machines (SVM), random forests (RF), linear regression, Naive Bayes, decision trees (DT) categorize pre-processed sets. Performance metrics like accuracy, precision, recall, f1-score calculate performance algorithms.

Language: Английский

Evaluation and downstream effects of household and industrial effluents discharge on some physicochemical parameters and surface Water Quality Index of River Mahanadi, Odisha, India DOI Creative Commons
Abhijeet Das

Discover Water, Journal Year: 2025, Volume and Issue: 5(1)

Published: April 21, 2025

Language: Английский

Citations

0
Insight into Urban River Water Quality Using Ecological Risk Assessment Based on Risk Quotient DOI
Bhesh Kumar Karki, Ligy Philip, Kajiram Karki

et al.

Water Conservation Science and Engineering, Journal Year: 2024, Volume and Issue: 9(2)

Published: Aug. 23, 2024

Language: Английский

Citations

3
Impacts of seasonal variations and wastewater discharge on river quality and associated human health risks: A case of northwest Dhaka, Bangladesh DOI Creative Commons

Hazzaz Bin Hassan,

Md. Moniruzzaman,

Ratan Kumar Majumder

et al.

Heliyon, Journal Year: 2023, Volume and Issue: 9(7), P. e18171 - e18171

Published: July 1, 2023

Surface water pollution caused by the discharge of effluents from industrial estates has become a major concern for Dhaka (Bangladesh). This study aims to have concise look at severe river pollution, mainly discharged tannery village. Effluent samples were collected five ejected points, including central effluent treatment plant (CETP), twenty adjacent water, and two pond nearby Hemayetpur, Savar. Thirty-one parameters been observed these sampling points three seasons, April 2021 January 2022. The results obtained quality indices, i.e., index (WQI), entropy (EWQI), irrigation (IWQI), show that most studied surface ranked "unsuitable" consumption, irrigation, anthropogenic purposes. highest health risk was downstream Hemayetpur city Savar CETP site, indicating higher levels heavy metal in following Carcinogenic non-carcinogenic human risks could be triggered consumption as concentrations arsenic (As), chromium (Cr), nickel (Ni), lead (Pb) exceeded upper benchmark 1 × 10−4 adults children. carcinogenic assessment revealed children more vulnerable hazards, quick corrective action is required control increased metals all sample locations. Therefore, through bioaccumulation, environment are affected areas. Using household work, or even purposes not advisable. study's result highlighted properly implementing compatible policies programs improve methods provide biodegradability Dhaleshwari River.

Language: Английский

Citations

8
A comprehensive assessment of gold leaching wastewater through Pollution and Water Quality Indices. Case study: Small scale extraction facilities in the department of Caldas - Colombia DOI Creative Commons
Guillermo H. Gaviria, Miguel Ángel Gómez García, Izabela Dobrosz‐Gómez

et al.

Results in Engineering, Journal Year: 2024, Volume and Issue: unknown, P. 103260 - 103260

Published: Oct. 1, 2024

Language: Английский

Citations

2
An IoT and machine learning solutions for monitoring agricultural water quality: a robust framework DOI Creative Commons
Mushtaque Ahmed Rahu, Muhammad Mujtaba Shaikh, Sarang Karim

et al.

Mehran University Research Journal of Engineering and Technology, Journal Year: 2023, Volume and Issue: 43(1), P. 192 - 192

Published: Dec. 30, 2023

All living things, comprising animals, plants, and people require water to survive. The world is covered in water, just 1 percent of it fresh functional. importance value freshwater have increased due population growth rising demands. Approximately more than 70 the world's used for agriculture. Agricultural employees are least productive, inefficient, heavily subsidized users world. They also utilize most overall. Irrigation consumes a considerable amount water. field's supply needs be safeguarded. A critical stage estimating agricultural production crop irrigation. global shortage serious issue, will only get worse years come. Precision agriculture intelligent irrigation solutions that solve aforementioned issues. Smart systems other modern technologies must improve quantity high-quality Such system has potential quite accurate, but requires data about climate quality region where used. This study examines smart using Internet Things (IoT) cloud-based architecture. water's temperature, pH, total dissolved solids (TDS), turbidity all measured by this device before processed cloud range machine learning (ML) approaches. Regarding content limits, farmers given accurate information. Farmers can increase effective techniques. ML methods support vector machines (SVM), random forests (RF), linear regression, Naive Bayes, decision trees (DT) categorize pre-processed sets. Performance metrics like accuracy, precision, recall, f1-score calculate performance algorithms.

Language: Английский

Citations

6