مجلة الاربعين المحكمة
The Arbaeen pilgrimage in Iraq’s Karbala is an officially acknowledged one of the world’s largest religious events, with millions of pilgrims visiting annually. The pilgrimage has major logistic and environmental issues due to the fast-growing scale. Here, we present a quantitative forecasting methods for visitor volumes and projecting necessary logistical materials based on socio-economic and environmental factors during the period 1991-2023. Data were collected from open-access global databases like the World Bank and supplemented with official Arbaeen visitor reports. We applied both linear regression and long short-term memory (LSTM) models to forecast visitor trends and estimate infrastructure demands such as water volume, tankers, and generators. The LSTM model demonstrated superior predictive accuracy in imitating temporal changes compared to linear regression. Regression models relating visitors to logistics yielded consistent estimators, which allowed the estimation of needed resources for future use, such as a 25-million-visitor event. The study also introduced indicators of resource usage sustainability, such as per-visitor water use and infrastructure load. Our findings demonstrate the strength of artificial intelligence for enhanced planning accuracy and sustainable resource usage for mass religious events.