Artificial intelligence based classification for waste management: A survey based on taxonomy, classification & future direction

Abstract

Waste management has grown to become one of the leading global challenges due to the massive generation of thousands of tons of waste that is produced daily, leading to severe environmental degradation, the risk of public health, and resource depletion. Despite efforts directed towards solving these problems, traditional methods of sorting and categorizing waste are inefficient and unsustainable, thus requiring the conceptualization of innovative AI-based solutions for more effective waste management. This review presents, a comprehensive review of all the strategies which are critical for AI based techniques, thus improve productivity and sustainability in operations. Diverse datasets used to train AI models along with performance evaluation metrics, and discusses challenges of AI assimilation in waste management systems, most fundamentally the issue of data privacy and concern of bias in the algorithms. Additionally, the role of loss functions and optimizers in enhancing AI model performance and suggests future research opportunities for sustainable resource recovery, recycling, and reuse based on AI.