Traffic accidents caused by excessive speeding presented critical safety challenges globally. This research aimed to develop an intelligent speed monitoring device that provided contextual warnings based on road type classifications. The study employed the ADDIE methodology encompassing analysis, design, development, implementation, and evaluation phases. Initial analysis identified hardware requirements including Arduino Nano microcontroller, GPS Ublox NEO 6M module, LCD display, and buzzer systems. The design phase established dual-mode operation algorithms for regular roads and highways with distinct speed thresholds. Development involved physical prototype construction and software programming using Arduino IDE. Implementation testing demonstrated GPS accuracy of 98.98% with average deviation of 2.20 km/h. The system successfully differentiated between road types and provided appropriate warnings through visual and auditory alerts. Field testing revealed 100% operational accuracy across multiple speed ranges in both regular road advisory mode and highway warning mode. The device effectively modified driver behavior by providing immediate feedback when speed limits were exceeded. Results indicated significant potential for reducing traffic accidents through real-time speed management. The system's dual-mode functionality addressed varying speed requirements across different road infrastructures, contributing to enhanced traffic safety protocols.
Shofiah et al. (2026) studied this question.
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