Wambo44-master/Ngao-Labs-Capstone-Project

This project applies data science and artificial intelligence techniques to analyze accident patterns in Kenya using official government datasets from the Kenya National Bureau of Statistics (KNBS) and the National Transport and Safety Authority (NTSA). # Ngao-Labs-Capstone-Project This project applies data science and artificial intelligence techniques to analyze accident patterns in Kenya using official government datasets from the Kenya National Bureau of Statistics (KNBS) and the National Transport and Safety Authority (NTSA). Despite pedestrian safety being a critical public health and transportation issue in Kenya, current road safety strategies lack comprehensive data-driven analysis of pedestrian accident patterns. Key questions remain unanswered: - What share of road casualties involves pedestrians? - Are pedestrians more likely to die in accidents compared to drivers, passengers, or motorcyclists? - Have pedestrian casualty and fatality trends improved or worsened over the past decade? - Which counties bear the highest pedestrian accident burden? Without answers to these questions, policymakers and transport authorities cannot effectively allocate limited resources or design targeted interventions. Road safety initiatives often rely on assumptions rather than empirical evidence, leading to inefficient spending and preventable loss of life. This project addresses this gap by developing a data-driven analysis that quantifies pedestrian risk patterns and provides evidence-based recommendations for road safety improvement. The findings will help answer the critical question: Where should Kenya focus its pedestrian safety efforts to achieve the greatest impact? Live Demo : ngao-labs-capstone-project-…