Low-Cost IoT Platforms for Urban Slum Environmental Monitoring in Nigeria

Urban slums in Nigeria face significant environmental challenges such as air pollution, water contamination, and waste management issues. These conditions often lead to health problems and hinder sustainable development. We propose a hybrid architecture combining Arduino microcontrollers, wireless sensors, and cloud-based analytics services. Data collected will be used for predictive analysis of air quality and waste management needs. Initial pilot studies in selected slums show that the IoT system can accurately monitor particulate matter levels with an average error rate below 5%. The proposed low-cost IoT solution demonstrates potential as a scalable tool for environmental monitoring in urban slum settings, offering significant cost savings and improved data accuracy. Communities should be engaged to ensure the sustainability of these systems. Public-private partnerships can facilitate wider deployment and maintenance of the platforms. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.