This assignment focuses on evaluating the role and impact of smart, IoT-based waste segregation systems in urban African settings. The study aims to assess how Internet of Things (IoT) technologies—such as sensor-enabled bins, data tracking, and mobile notifications—can improve waste collection efficiency, promote recycling, and influence citizen behavior towards proper waste segregation.
Key Objectives:
- To explore the current state of waste segregation practices in selected African towns and the challenges faced, such as informal dumping, lack of awareness, and inadequate infrastructure.
- To examine how IoT-based smart bins can monitor fill levels, identify types of waste (organic, plastic, metal, e-waste), and send real-time data to waste management authorities.
- To assess the impact on user behavior, such as increased recycling rates, improved waste disposal habits, and public engagement through feedback systems (e.g., mobile apps or incentive programs).
- To evaluate the system’s operational efficiency, including optimized collection routes, cost savings, reduced overflow, and environmental benefits.
- To provide recommendations for scalable implementation, considering socio-economic, technical, and policy constraints in the African context.
Methodology:
- Literature review of existing smart bin projects globally and in Africa (e.g., in South Africa, Nigeria, Kenya).
- Case study analysis or simulation model (if data is available) of IoT bin deployment in a chosen town.
- Stakeholder interviews or hypothetical behavior change model based on community engagement strategies.
- Data analysis (e.g., comparative efficiency metrics, bin usage rates, user response data if available).
Expected Outcome:
A critical and evidence-based evaluation of the potential of IoT-driven waste segregation systems to revolutionize municipal waste management in African towns. The assignment will present practical insights into how technology and behavior change can align to create cleaner, smarter, and more sustainable urban environments