Waste management in developing countries faces several challenges, including optimizing basic services and integrating sustainable innovations. However, local empirical studies that could guide this transition are often lacking. This study analyses residents' perceptions of household waste management in the city of Bukavu, comparing traditional methods and automated systems. A probabilistic survey of 442 households across the city was conducted using mobile data collection (KoboCollect). Data were analyzed quantitatively using the Python programming language in the Google Colab environment. While a structured municipal service exists (used by 82.8% of households), satisfaction is only relative (57.2%). Critical health concerns are odors (86.9%) and disease proliferation (84.8%). Residents prioritize increasing collection frequency (78.5%) and providing public bins (76%). Although 53.6% believe their neighborhood is ready for automation, major concerns regarding job losses (66.1%) and cost (59%) persist. The study provides a three-level empirical roadmap: it diagnoses the need to optimize an existing service, delivers a citizen-centered action plan for immediate improvements, and defines the social and informational prerequisites for a sustainable automation transition. Success requires improving basic services while managing the perceived socioeconomic risks of innovation.