2025/03/04 by AIT OUBBA, Zahra, OUNINI, Khadija, CHERROUD, Sanaa +2
#Artificial intelligence #Composting #Computational thinking #IoT #Process optimization #Waste management
paper · doi:10.48402/imist.prsm/jasab-v6i2.55184
Composting organic waste plays a crucial role in waste management and greenhouse gas reduction. However, this natural process is influenced by many factors, such as temperature, humidity, and aeration, which require optimized management to ensure its effectiveness. This study explores the integration of computational thinking in composting, using advanced technologies such as artificial intelligence (AI), IoT sensors, and predictive modeling to improve the management of key composting parameters. The main objective is to optimize the composting process by reducing human errors and accelerating the production of quality compost. The methodology is based on an analysis of existing case studies and the collection of data from academic research, providing an overview of the applications of computational thinking in composting. The results reveal that the use of IoT sensors and AI algorithms has allowed better control of the environmental conditions of composting, improving process management. This study shows that the integration of computational thinking offers sustainable ecological and economic solutions. It paves the way for large-scale applications in waste management, promoting smarter and more efficient composting practices.