Article Per Year (5 Year)
p-Index From 2021 - 2026
0.408
P-Index
This Author published in this journals
All Journal Journal of Multidisciplinary Science: MIKAILALSYS International Journal of Education, Management, and Technology
Paul, Chadi
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Education Electrical & Electronics Engineering Engineering Environmental Science Materials Science & Nanotechnology Physics Social Sciences Other

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Intelligent Recycling Facilities with IoT Sensors and Data Analytics for Environmental Justice and Sustainable Materials Processing in Low-Income Areas Akintayo, Taiwo Abdulahi; Enabulele, Ewemade Cornelius; Paul, Chadi; Okereke, Ruth Onyekachi; Sobajo, Moses Sodiq; Afolabi, Olasunkanmi John; Joel, Ogundigba Omotunde; Nnadiekwe, Oluchi Anthonia; Queenet, Madumere Chiamaka; Abdulyekeen, Rilwan; Emoshoriemhe, Akpaibor Favour; Oyefemi, Oyero Muqadas; Godwin, Agbonze Nosa; Ebuka, Eguzoroh Emmanuel
Journal of Multidisciplinary Science: MIKAILALSYS Vol 2 No 3 (2024): Journal of Multidisciplinary Science: MIKAILALSYS
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/mikailalsys.v2i3.3827

Abstract

This research seeks to transform waste management in low-income communities like Nigeria by introducing intelligent recycling facilities equipped with IoT sensors and data analytics. These innovative facilities will optimize recycling processes, monitor material flows, and provide valuable insights on waste reduction and environmental impact. The goal is to address the pressing issue of waste production, which has become a significant concern in developing nations due to rising food consumption and population growth. In Nigeria, inadequate waste collection and disposal methods have led to environmental pollution and health crises. The common practice of dumping garbage on roads has resulted in unsightly piles of refuse, hindering the nation's beauty. To combat this, we propose the adoption of sustainable smart bins with efficient IoT applications. These smart bins will provide a futuristic solution for waste management, enabling remote monitoring and optimization of waste levels. The benefits of this IoT-based system include (1) Remote access for efficient level control (2) Improved time and energy efficiency (3) Reduced congestion in waste bins. By developing a low-cost, intelligent waste bin system with IoT technology, we can create a green and clean atmosphere within cities. This innovative approach will inform policy and practice, advancing environmental justice and sustainable development in marginalized areas.
Transforming Data Analytics with AI for Informed Decision-Making Akintayo, Taiwo Abdulahi; Paul, Chadi; Queenet, Madumere Chiamaka; Nnadiekwe, Oluchi Anthonia; Victoria, Shittu Sarah; David, Fakokunde Babatunde; Joel, Ogundigba Omotunde; Agada, Olowu Innocent; Ngozi, Egenuka Rhoda; Arinze, Ugochukwu Ukeje; Ojemerenvhie, Grace Alele; Oluwadamilola, Adebesin Adedayo; Nnamani, Chinenye Cordelia; Olayinka, Usman Wasiu
International Journal of Education, Management, and Technology Vol 2 No 3 (2024): International Journal of Education, Management, and Technology
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/ijemt.v2i3.3812

Abstract

This study delves into how advanced data analytics and artificial intelligence (AI) can work together to enhance decision-making processes. As we navigate today’s data-driven environment, discovering the synergy between these fields is crucial, given the growing complexity of datasets. Advanced analytical tools are essential, and AI offers exceptional capabilities in pattern recognition and automation. This research investigates how cosmbining data analytics techniques—such as Predictive Modeling, Clustering, and Trend Analysis—with AI approaches like Machine Learning and Deep Learning can improve decision-making. A key focus of the study is on making AI models more interpretable and transparent. It emphasizes the importance of ensuring that AI-driven decisions are clear and understandable. Additionally, the research addresses ethical considerations and the need for human-centered design, aiming to balance AI’s power with openness. It also strives for responsible AI use by tackling issues such as bias and promoting ethical practices in the application of advanced data analytics and AI. The study demonstrates practical applications in areas like healthcare and finance, showing how these technologies can transform personalized medicine, disease prediction, risk assessment, fraud detection, and market trend analysis. Overall, this research highlights the valuable interaction between advanced data analytics and AI, offering a guide for organizations to enhance their decision-making while adhering to ethical standards and responsible AI use.
Co-Authors Abdulyekeen, Rilwan Afolabi, Olasunkanmi John Agada, Olowu Innocent Akintayo, Taiwo Abdulahi Arinze, Ugochukwu Ukeje David, Fakokunde Babatunde Ebuka, Eguzoroh Emmanuel Emoshoriemhe, Akpaibor Favour Enabulele, Ewemade Cornelius Godwin, Agbonze Nosa Joel, Ogundigba Omotunde Ngozi, Egenuka Rhoda Nnadiekwe, Oluchi Anthonia Nnamani, Chinenye Cordelia Ojemerenvhie, Grace Alele Okereke, Ruth Onyekachi Olayinka, Usman Wasiu Oluwadamilola, Adebesin Adedayo Oyefemi, Oyero Muqadas Queenet, Madumere Chiamaka Sobajo, Moses Sodiq Victoria, Shittu Sarah