Low-Cost IoT Frameworks for Urban Slum Environmental Monitoring in Tanzania: A Comparative Analysis

Urban slums in Tanzania face significant environmental challenges such as air pollution, water contamination, and waste management issues. Traditional monitoring methods are often cost-prohibitive and time-consuming. A mixed-methods approach was employed, combining quantitative data from sensor readings with qualitative insights from interviews and surveys conducted among stakeholders in selected urban slums. A total of six different low-cost IoT frameworks were evaluated over a period of one year. The analysis revealed that the most cost-effective framework achieved an average reduction of 20% in air pollution levels compared to baseline conditions, with sensor accuracy within ±5%. The findings suggest that low-cost IoT solutions can significantly improve environmental monitoring in urban slums without substantial financial investment. This opens up opportunities for broader deployment and sustainability in resource-constrained settings. Public sector agencies should prioritise the adoption of these frameworks to enhance environmental governance in urban slums, while private sector entities could develop or fund pilot projects as a means of social responsibility. Low-Cost IoT, Urban Slum Monitoring, Environmental Quality, Tanzania 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.