Muhibbul Arman
Biographic Data
| ID | 6955339 |
|---|---|
| NAME | Muhibbul Arman |
| GIVEN NAMES | Muhibbul |
| FAMILY NAME | Arman |
| SIGNATURE | ARMAN M |
| AFFILIATIONS | University of New Haven |
| VERIFIED | No |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 3 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2024 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Big Data and Machine Learning for Sustainable Waste Reduction
Purpose: Climate change, rising resource costs, and global policy frameworks like the United Nations Sustainable Development Goals (SDGs) are putting more and more pressure on businesses to adopt sustainable practices. This paper examines the integration of Big Data, data analytics, machine learning (ML), and waste-management strategies to mitigate waste and enhance sustainability across various industries.Methodology: A systematic literature rev…
Big Data and Machine Learning for Sustainable Waste Reduction
Purpose: Climate change, rising resource costs, and global policy frameworks like the United Nations Sustainable Development Goals (SDGs) are putting more and more pressure on businesses to adopt sustainable practices. This paper examines the integration of Big Data, data analytics, machine learning (ML), and waste-management strategies to mitigate waste and enhance sustainability across various industries.Methodology: A systematic literature rev…
Big Data and Machine Learning for Sustainable Waste Reduction
Purpose: Climate change, rising resource costs, and global policy frameworks like the United Nations Sustainable Development Goals (SDGs) are putting more and more pressure on businesses to adopt sustainable practices. This paper examines the integration of Big Data, data analytics, machine learning (ML), and waste-management strategies to mitigate waste and enhance sustainability across various industries.Methodology: A systematic literature rev…
No prominent works on this page.
Big Data and Machine Learning for Sustainable Waste Reduction
Purpose: Climate change, rising resource costs, and global policy frameworks like the United Nations Sustainable Development Goals (SDGs) are putting more and more pressure on businesses to adopt sustainable practices. This paper examines the integration of Big Data, data analytics, machine learning (ML), and waste-management strategies to mitigate waste and enhance sustainability across various industries.Methodology: A systematic literature rev…
Big Data and Machine Learning for Sustainable Waste Reduction
Purpose: Climate change, rising resource costs, and global policy frameworks like the United Nations Sustainable Development Goals (SDGs) are putting more and more pressure on businesses to adopt sustainable practices. This paper examines the integration of Big Data, data analytics, machine learning (ML), and waste-management strategies to mitigate waste and enhance sustainability across various industries.Methodology: A systematic literature rev…
Big Data and Machine Learning for Sustainable Waste Reduction
Purpose: Climate change, rising resource costs, and global policy frameworks like the United Nations Sustainable Development Goals (SDGs) are putting more and more pressure on businesses to adopt sustainable practices. This paper examines the integration of Big Data, data analytics, machine learning (ML), and waste-management strategies to mitigate waste and enhance sustainability across various industries.Methodology: A systematic literature rev…
Analytics (3 works) · Big data (3 works) · Internet of Things and AI (3 works) · Resource Efficiency (3 works) · Sustainability (3 works) · Investment (military (2 works) · Sustainable development (2 works) · Digital and Traditional Archives Management (1 work) · Investment (military) (1 work) · Library Science and Administration (1 work)