The Performance of Artificial Intelligence-based Earthquake Early Warning System and Structural Health Monitoring in the Bekasi Earthquake of August 20, 2025: A Case Study of President University Building A

Abstrak

Abstract Earthquakes are a natural disaster that can significantly impact human safety and the continued functionality of buildings, particularly in densely populated urban areas like Bekasi. The earthquake that occurred in Bekasi on August 20, 2025, at 7:55 PM WIB (Western Indonesian Time) marked a significant milestone in the field testing of the On-Site Artificial Intelligence-based On-Site Earthquake Early Warning System (AI-EEWS) and Structural Health Monitoring (SHM), the first comprehensive installation in Indonesia. This system has been implemented since August 2023 at Building A of President University, using three A222 seismic sensors placed within the building structure. Test results showed that the system successfully provided an early warning 2.4 seconds before the peak ground acceleration (PGA). The system predicted an earthquake intensity of IV on the MMI scale, which was consistent with the field-measured intensity. Furthermore, the SHM analysis indicated that the structure of Building A was safe, with no significant damage, allowing the building to resume normal use after the earthquake. These findings demonstrate that the combination of AI-EEWS and SHM technology can provide tangible benefits in disaster risk mitigation, both by providing valuable early warning time and by ensuring the health of buildings after an earthquake. This study opens up significant opportunities for widespread application of the system to critical infrastructure in Indonesia, thereby improving community preparedness and reducing potential losses from earthquakes, particularly in residential and industrial areas.

Identifier

• DOI: https://doi.org/10.1088/1755-1315/1607/1/012035
• OpenAlex: https://openalex.org/W7153080011