Comparative Analysis of Three Solid Waste Management Systems Towards Full Automation - Omiyale, Abolade David; Ogunwolu, Ladi F.; Ajibola, Olawale Olaniyi (International Journal of Applied Sciences and Smart Technologies, 2024)
This study uses a four-week simulation to evaluate traditional, semi-automatic, and autonomous waste management systems, employing Principal Component Analysis (PCA), Discrete Event Simulation (DES), and an ANOVA test. PCA was used to visualise and understand the variations in waste collection volumes between the three systems, with the first two principal components accounting for 100% of the variance (PC1: 56.3%, PC2: 43.7%). Each system was classified into distinct clusters: traditional in the lower-left quadrant, semi-automatic in the upper-left and lower-right quadrants, and autonomous in the upper-right quadrant, with ANOVA indicating significant variations. DES simulated everyday waste collection for 120 days. The traditional system collected an average of 50 kg/day with a 10-kilogramme variance, the semi-automatic 48 kg/day with an 8 kg variability, and the autonomous 45 kg/day with a 5 kg variability. The total waste collected was 6012.34 kg (traditional), 5824.29 kg (semi-automatic), and 5482.67 kg (autonomous). Fuel consumption, cost savings, and environmental impacts were analyzed. The autonomous system showed the lowest fuel consumption and highest cost savings, significantly reducing carbon emissions compared to others. The results from PCA and DES, supported by ANOVA, indicate that while the traditional system is most efficient in waste collection, the autonomous system offers consistent performance and significant environmental benefits. This comprehensive analysis provides valuable insights for optimizing waste management strategies and balancing efficiency, cost, and environmental impact. Keywords: Solid waste management, Autonomous systems, urbanization, environmental impact, and Sustainability.