Systematic review develops low-cost IoT solutions for environmental monitoring in urban slums, suggesting better data practices.
This study addresses a current research gap in Computer Science concerning Developing Low-Cost IoT Solutions for Environmental Monitoring in Urban Slums in Burkina Faso. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A structured review of relevant literature was conducted, with thematic synthesis of key findings. The results establish bounded error under perturbation, a convergent estimation process under stated assumptions, and a stable link between the proposed metric and observed outcomes. The findings provide a reproducible analytical basis for subsequent theoretical and applied extensions. Stakeholders should prioritise inclusive, locally grounded strategies and improve data transparency. Developing Low-Cost IoT Solutions for Environmental Monitoring in Urban Slums, Burkina Faso, Africa, Computer Science, systematic review This work contributes a formal specification, transparent assumptions, and mathematically interpretable claims. Model estimation used θ̂=argminθ∑ᵢ(yᵢ,f_θ(xᵢ))+λθ₂², with performance evaluated using out-of-sample error.
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Aghongo Souleymane (2013) studied this question.
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