Abdalla, Olla and Ahmad Tajuddin, Husna and Jami, Mohammed Saedi (2023) Ai-based waste management optimization in the halal food industry of Malaysia: a mini review. Chemical and Natural Resources Engineering Journal, 7 (2). pp. 30-42. E-ISSN 2637-0719
|
PDF
- Published Version
Download (4MB) | Preview |
Abstract
Solid waste management (SWM) has become a critical issue in Malaysia, with increasing amounts of waste generated every year and limited resources available to manage it effectively. Additionally, the halal food industry is rapidly growing and expanding globally due to the rising Muslim population, predicted to reach 2.2 billion by 2030 at an annual growth rate of 1.5 percent. This increasing production and consumption of halal food has an impact on the environment. Artificial intelligence (AI) has the potential to revolutionize solid waste management by improving efficiency, reducing costs, and optimizing waste management processes. This mini review provides an overview of the impact of AI on solid waste management in Malaysia, focusing on the current trends, challenges, and opportunities in the industry, particularly in the halal food sector. The review offers insights into the potential of AI in enhancing waste collection, optimizing waste management processes, improving resource recovery and recycling, and reducing waste to landfill. Additionally, the review explores the current initiatives, projects, and developments in the field of AI and solid waste management in Malaysia and identifies areas for future research and collaboration. The review concludes that AI has a significant role to play in improving solid waste management in Malaysia, and continued investment and development in this area is necessary to achieve sustainable waste management practices. Furthermore, its findings have the potential for wider applications and inspire future research in AI-based waste management solutions across various industries. The findings and recommendations of this review have the potential to be adapted and implemented in other industries facing similar waste management challenges
| Item Type: | Article (Journal) |
|---|---|
| Uncontrolled Keywords: | Artificial intelligence, Machine Learning, Halal food waste, Sustainable waste management, Malaysia |
| Subjects: | T Technology > TA Engineering (General). Civil engineering (General) > TA170 Environmental engineering. Sustainable engineering T Technology > TA Engineering (General). Civil engineering (General) > TA177.4 Engineering economy T Technology > TD Environmental technology. Sanitary engineering > TD159 Municipal engineering T Technology > TD Environmental technology. Sanitary engineering > TD920 Rural and farm sanitary engineering |
| Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): | Kulliyyah of Engineering > Department of Biotechnology Engineering |
| Depositing User: | Dr Husna Ahmad Tajuddin |
| Date Deposited: | 25 Feb 2026 16:07 |
| Last Modified: | 25 Feb 2026 16:07 |
| Queue Number: | 2026-02-Q2339 |
| URI: | http://irep.iium.edu.my/id/eprint/127654 |
Actions (login required)
 |
View Item |
Download Statistics
Download Statistics