Artificial intelligence and IoT driven technologies for environmental pollution monitoring and management

SM Popescu, S Mansoor, OA Wani… - Frontiers in …, 2024 - frontiersin.org
Detecting hazardous substances in the environment is crucial for protecting human
wellbeing and ecosystems. As technology continues to advance, artificial intelligence (AI) …

Fluoride and nitrate enrichment in coastal aquifers of the Eastern Province, Saudi Arabia: The influencing factors, toxicity, and human health risks

SI Abba, JC Egbueri, M Benaafi, J Usman, AG Usman… - Chemosphere, 2023 - Elsevier
Fluoride and nitrate contamination of groundwater is a major environmental issue in the
world's arid and semiarid regions. This issue is severe in both developed and develo** …

Fractionation of dyes/salts using loose nanofiltration membranes: Insight from machine learning prediction

N Baig, J Usman, SI Abba, M Benaafi… - Journal of Cleaner …, 2023 - Elsevier
Wastewater (WW) served as the crucial indicator for sustainable development, human
health, and the ecosystem. Nanofiltration (NF) membranes are efficient in contaminants, dye …

Nitrate concentrations tracking from multi-aquifer groundwater vulnerability zones: Insight from machine learning and spatial map**

SI Abba, MA Yassin, MM Jibril, B Tawabini… - Process Safety and …, 2024 - Elsevier
Nitrate contamination in groundwater is a significant environmental concern that poses risks
to human health and ecosystems. Several goals and targets of Sustainable Development …

ChatGPT and the future of impact assessment

M Khan, MN Chaudhry, M Ahsan, R Ahmad - Environmental Science & …, 2024 - Elsevier
Like all other fields, Artificial Intelligence (AI) is expected to affect the Impact Assessment (IA)
systems worldwide. This study explores the opinions and concerns of international IA …

Intelligent process optimisation based on cutting-edge emotional learning for performance evaluation of NF/RO of seawater desalination plant

SI Abba, M Benaafi, IH Aljundi - Desalination, 2023 - Elsevier
As decision-makers, researchers encounter highly dynamic, complex problems requiring
suitable nature-based and industrial quantitative tools for performance analyses, syntheses …

Ensemble hybrid machine learning to simulate dye/divalent salt fractionation using a loose nanofiltration membrane

N Baig, SI Abba, J Usman, M Benaafi… - Environmental Science …, 2023 - pubs.rsc.org
The escalating quantity of wastewater from multiple sources has raised concerns about both
water reuse and environmental preservation. Therefore, there is a pressing need for …

Genetic neuro-computing model for insights on membrane performance in oily wastewater treatment: An integrated experimental approach

J Usman, SI Abba, NB Ishola, T El-Badawy… - … Research and Design, 2023 - Elsevier
In this study, response surface methodology (RSM) and artificial neural network-based
genetic algorithm (ANN-GA) were utilized to predict two crucial output parameters of …

Tracking the impact of heavy metals on human health and ecological environments in complex coastal aquifers using improved machine learning optimization

AM Jibrin, SI Abba, J Usman, M Al-Suwaiyan… - … Science and Pollution …, 2024 - Springer
The rising heavy metal (HM) pollution in coastal aquifers in rapidly urbanizing areas such as
Dammam leads to significant risks to public health and environmental sustainability …

Global big data laboratory experiment, integrated with kernel-based algorithm with an improved nonlinear ensemble for compressive strength modeling

BA Salami, J Usman, A Gbadamosi, SI Malami… - Scientific Reports, 2024 - nature.com
With the continuous clamor for a reduction in embodied carbon in cement, rapid solution to
climate change, and reduction to resource depletion, studies into substitute binders become …