Monitoring Migrant Labors by Using Decision Tree

The monitoring of migrant laborers is a significant challenge in various industries. The lack of structured data collection and performance analysis often leads to inefficiencies, wage disputes, and insecure working conditions. Decision Tree algorithms provide a powerful analytical tool for evaluating workers’ performance based on collected data such as work hours and task completion status. This literature survey explores previous research on labor monitoring, workforce tracking, and decision tree applications in labor analytics. It explores various research studies and methodologies related to monitoring migrant laborers using Decision Tree algorithms. It highlights key challenges faced by migrant workers, existing monitoring systems, and how decision tree models can improve workforce management.