Rain Attenuation Statistics and Educational Connectivity: A Case Study of UTHM for Resilient E-Learning Infrastructure

As universities worldwide transition toward digital education, institutions in tropical regions face a distinct and pressing challenge: their heavy reliance on wireless internet is frequently disrupted by intense seasonal rainfall. This study underscores the vital importance of integrating localized climate data into educational technology planning. Using four years of high-resolution rainfall measurements from an on-campus weather station at Universiti Tun Hussein Onn Malaysia (UTHM), we developed probabilistic models (Complementary Cumulative Distribution Functions) essential for designing reliable campus networks. Our analysis identified a critical shortcoming in the ITU-R P.837-8 international standard, which significantly underestimates peak rainfall rates in this region. For instance, at the critical 0.01% exceedance level used for link budgeting, the measured rain rate was 125.02 mm/h, compared to the ITU-predicted value of 94.5 mm/h, an underestimation of 32.3%. Unquestioned adoption of this model results in an internet infrastructure ill-suited to local conditions, leading to recurrent service failures. For students and instructors, these interruptions manifest as frozen video lectures, unsuccessful assignment submissions, and loss of access to essential digital resources, ultimately worsening educational inequality. We argue for a strategic shift in institutional approach, demonstrating that feasible, campus-based meteorological monitoring provides the necessary data. Implementing a data-informed strategy is indispensable for minimising disruptions, ensuring equitable access, and sustaining digital education in tropical regions.