KAJIAN LITERATUR SISTEMATIS INTEGRASI DATA JEMBATAN BAJA UNTUK SMART INFRASTRUCTURE

Abstrak

Infrastruktur jembatan baja menuntut sistem pemantauan berkelanjutan berbasis data secara real-time. Kajian literatur sistematis ini bertujuan memetakan perkembangan penelitian dan mengidentifikasi kesenjangan pengetahuan dalam domain integrasi data jembatan baja untuk smart infrastructure. Metodologi mengacu pada protokol PRISMA 2020 yang dipadukan dengan analisis bibliometrik menggunakan VOSviewer dan R Studio. Dari 18.571 dokumen awal pada basis data Scopus, Web of Science, dan IEEE Xplore, diperoleh 50 artikel final dengan rentang publikasi 2021–2025. Hasil analisis mengidentifikasi empat kluster penelitian utama: IoT dan Structural Health Monitoring, Artificial Intelligence dan Data Fusion, Digital Twin dan BIM, serta Interoperabilitas dan Standardisasi. Lima research gap sistemik teridentifikasi, meliputi ketiadaan framework integrasi vertikal end-to-end, absennya protokol interoperabilitas lintas platform, minimnya validasi spesifik pada jembatan baja, dan lemahnya koneksi antara output analitik AI dengan sistem keputusan pemeliharaan otomatis. Sebagai respons, tiga novelty dirumuskan: Layered Data Integration Framework, Steel-Aware Adaptive Data Fusion Model, dan Smart Bridge Interoperability Ontology (SBIO). Temuan kajian ini diharapkan menjadi landasan bagi pengembangan ekosistem smart infrastructure jembatan baja yang terintegrasi dan terstandardisasi.

Steel bridge infrastructure demands continuous real-time data-driven monitoring systems. This systematic literature review aims to map research developments and identify knowledge gaps in steel bridge data integration for smart infrastructure. The methodology follows the PRISMA 2020 protocol combined with bibliometric analysis using VOSviewer and R Studio. From 18,571 initial documents across Scopus, Web of Science, and IEEE Xplore, 50 final articles within the 2021–2025 publication window were obtained. Analysis identified four major research clusters: IoT and Structural Health Monitoring, Artificial Intelligence and Data Fusion, Digital Twin and BIM, and Interoperability and Standardization. Five systemic research gaps were identified, including the absence of an end-to-end vertical integration framework, lack of cross-platform interoperability protocols, insufficient validation on steel bridges specifically, and weak linkage between AI analytical outputs and automated maintenance decision systems. Three novelties are proposed in response: a Layered Data Integration Framework, a Steel-Aware Adaptive Data Fusion Model, and a Smart Bridge Interoperability Ontology (SBIO). These findings are intended as a foundation for developing an integrated and standardized smart infrastructure ecosystem for steel bridges.