Wyniki wyszukiwania - BazTech

Ograniczanie wyników

2 2020

Powiadomienia systemowe

Sesja wygasła!

Znaleziono wyników: 2

Liczba wyników na stronie

Wyniki wyszukiwania

Wyszukiwano:
w słowach kluczowych: Tigris river

Sortuj według:

Ogranicz wyniki do:

Internet of Things (IoT) and Artificial Neural Networks Towards Water Pollution Forecasting

Ibrahim Thaer, Mishra Alok

Rocznik Ochrona Środowiska

2020

Tom 22, cz. 1

117--129

Water could be some-times a source of danger on people's lives and property. Although it is one of the most important elements of life on this planet. This article define the threat of water pollution in Tigris River in Iraq. by collecting a data that generated by sensors that installed in a water pollution sensing project in Baghdad city, also this article aimed to detect and analyze the behavior of water environment. It is an effort to predict the threat of pollution by using advanced scientific methods like the technology of Internet of Things (IoT) and Machine learning in order to avoid the threat and/or minimize the possible damages. This can be used as a proactive service provided by E-governments towards their own citizens.

Modeling of trihalomethane compounds formation in Baghdad water supply network

Ewaid Salam H., Al-Farhani Bassam F., Abed Salwan A., Al-Ansari Nadhir

Przegląd Naukowy Inżynieria i Kształtowanie Środowiska

2020

Vol. 29, No. 2

136--144

This study was conducted to measure the concentrations of four trihalomethane compounds (THMs) in raw, treated, and drinking water of seven water purification plants and the residential neighborhoods nearby in Baghdad. About 350 samples gathered between January and October 2017 and analyzed by the gas chromatography method. Results showed that THM annual levels in tap water ranged between 12 and 97.3 µg·l–1 in winter and summer consecutively, with a mean concentration of 60 µg·l–1, these concentrations did not exceed the level recommended by the WHO and the Iraqi standards. Statistical modeling by SPSS software for the formation of THM (the dependent factor) in the water supply network was undertaken using the measured water quality parameters (as independent factors) and utilizing multiple regression analysis. The model obtained has a high correlation (r = 0.842) and approved that the most affecting parameters on THM formation are total organic carbon, temperature, turbidity, total solids, and chlorine dose. The model that was derived may be used for the purposes of choosing appropriate THM-reduction procedures and the use of chlorine for improving the method of disinfection.