Smartphone data streams for bridge health monitoring

Knowledge on the dynamic properties of bridges in a city can improve condition assessments, maintenance scheduling, and emergency planning to better serve the public. Currently, bridge vibration data is obtained primarily by researchers through the use of a sophisticated sensor network that is composed of fixed sensor nodes. Recent studies have supported the alternative of mobile sensor networks, which are capable of delivering important structural information, e.g., modal properties, requiring less setup efforts and using fewer sensors. Simultaneously, digital technology has spawned data initiatives such as crowdsensing, in which individuals can collectively sense the urban environment. The prevalence of smartphones, which contain various advanced sensors, is rapidly restructuring researchers' perceptions of data collection. This paper discusses the confluence of these emerging technologies, which can provide regular infrastructure data streams, within structural health monitoring (SHM) procedures for the immediate goal of system identification (SID) and towards automated maintenance of bridges. Will researchers continue to install sensor networks and collect their own data or will they start to source resident smartphone data? One of the objectives of this ongoing work is to quantify expected smartphone data stream volumes that would be applicable to SHM processes. As an example, the number of smartphones that traverse the Harvard bridge in a month is quantified.