Implementation of Early Warning System (EWS) Feature on Mobile Tower Battery in Realtime to Reduce Mobile Tower Downtime

Mobile tower network reliability at PT Antareja Mahada Makmur (AMM), Mifa Jobsite, was partially dependent on battery performance. However, the existing monitoring procedures relied on manual inspections, potentially delaying the detection of voltage drops, particularly during shift transitions. This study aimed to design, implement, and evaluate a real-time early warning system (EWS) for mobile tower batteries using an ESP32 microcontroller, applying the eight-step Quality Control Circle (QCC) methodology and the Plan–Do–Check–Act (PDCA) cycle. Operational records, field observations, team discussions, and cause-and-effect (fishbone) analysis were employed to identify the absence of automated battery monitoring and alert mechanisms as a primary operational issue. The developed system continuously monitored battery voltage and generated automatic notifications when voltage readings fell below 12 V in 12 V operating mode or 24 V in 24 V operating mode. Following implementation, monthly local area network (LAN) availability increased from 92.87% in January 2026 to 99.51% in April and remained at 99.49% in May 2026. Furthermore, no battery-related mobile tower downtime was recorded during the first week of April, compared with documented incidents during the corresponding period in January. These before-and-after findings indicated improvements in operational performance, although the observational design did not establish that the EWS alone caused the increase in network availability. The implementation demonstrated the potential of automated battery monitoring to facilitate earlier fault detection, accelerate maintenance responses, and support network reliability and preventive maintenance practices. Further research involving longer monitoring periods and additional battery health indicators was recommended to evaluate the system's sustained effectiveness and operational reliability.