Conventional trade-potential studies based on gravity models explain bilateral trade mainly through economic scale, population, income differences, and geographic distance, while paying limited attention to logistics and maritime information obtained from sensing-enabled monitoring systems. In digital logistics and smart-port environments, IoT devices, tracking-and-tracing systems, automatic identification system (AIS)-based vessel monitoring, and port monitoring platforms provide sensing-derived information on shipment visibility, cargo traceability, maritime connectivity, route availability, and port efficiency. However, a remaining problem is how such heterogeneous sensing-derived operational information can be systematically transformed into quantitative indicators and incorporated into conventional trade-potential models. Accordingly, the objective of this study is to examine whether sensing-related logistics and maritime operational information can improve gravity-based trade-potential assessment beyond conventional economic and geographic variables. To achieve this objective, a sensing-information-assisted framework is proposed by incorporating IoT-enabled logistics indicators and maritime sensing variables into an extended gravity model. Using panel data on five Portuguese-speaking countries’ exports to China from 2003 to 2022, the baseline gravity model is compared with models incorporating aggregated and disaggregated sensing-related indicators, including the IoT-enabled logistics sensing index (IOTLS), tracking-and-tracing capability (TRACE), AIS-based maritime connectivity (AISCON), port dwell time (DWELL), and shipping-route density (ROUTE). The results show that incorporating sensing-related indicators improves the explanatory performance of trade-potential assessment for total exports and major commodity categories. The disaggregated TRACE/ROUTE/DWELL specification outperforms the aggregate IOTLS/AISCON model, demonstrating the value of distinguishing individual sensing-derived operational components. A current limitation is the incomplete availability of historical AIS, port-operation, and shipment-level IoT datasets for the entire study period; therefore, consistently constructed and standardized sensing-related operational indicators are used to establish and evaluate the proposed framework. Further validation using high-resolution and directly observed sensing data remains an important issue for future research.