High-frequency ozone generators controlled by sensor network and modeling the process of groundwater purification from heavy metals

2025

Full text Open access: Gold Metadata (CSL-JSON)
DOI 10.1088/1755-1315/1491/1/012029
Data confidence 70 medium
How this score is calculated

It is built from checkable properties of the record itself: whether the article has a DOI, how many independent sources confirmed its data, whether the required fields are filled in, and how recent the latest confirmation is. Disagreement between sources and a missing identifier lower it. A value of 80 or above means the record was published without further checking; 60 to 79 means it is published at reduced confidence, with a manual check advisable. A record verified by an editor by hand is never pushed below 90 by a recalculation. This scores our data about the article, not the article itself.

Abstract

Abstract This study examines the process of groundwater purification from heavy metals through the control of high-frequency ozone generators using a sensor network. The use of high ozone concentrations allows for effective removal of heavy metals from water. The goal is to enhance the efficiency of the purification process by automating it through ozone generator control. The initial ozone concentration starts at zero and gradually reaches 2 mg/L over time. The initial concentration of heavy metals is 10 mg/L, and due to the impact of ozone, it is reduced to 0.2 mg/L. The sensor network ensured real-time adjustment of ozone levels, optimizing the process. As a result, purification efficiency increased by up to 60%. In addition to removing heavy metals, this method allowed for up to 20% energy savings. The modeling enabled prediction and optimization of the system’s operational parameters. Controlling the ozone concentration through sensor networks helped maintain process stability. The results demonstrated the significant role of ozone in the water purification process. This technology is important as an eco-friendly and efficient solution, offering possibilities for energy saving and water quality improvement. Automation of the system reduces human intervention and optimizes the process.