One of the most critical components of the US transport system is railroads: providing means of transportation for 48% of the nation's total modal tonnage. Despite such important tasks, more than half of the railroad bridges, the essential component of railroads to maintain flow of network, were built before 1920, making them the most fragile components of the railroad system. Wired and wireless sensor systems have been deployed, but none is designed specifically to address the challenges of railroad bridges monitoring, including: 1) limited energy source for sensors; 2) short and random nature of train schedule; 3) unavailable autonomous monitoring systems; and 4) difficult rapid decision-making process due to long data processing time. This paper focuses on efforts to develop an autonomous schedule-based framework for monitoring railroad bridges using wireless smart sensor network (WSSN). This framework, which bases on WSSN platform Xnode, makes use of multiple components, including hardware, software, and algorithms to fulfill the needs for railroad bridge condition monitoring. To demonstrate the efficacy of this system, a full-scale monitoring campaign has been conducted. With these improvements to overcome the challenges of monitoring railroad bridges, this system is expected to become an important tool for railroad engineers and decision makers.