About this Research Topic
Structures are increasingly being monitored for ensuring safety, for estimating remaining service life, and for taking appropriate retrofit actions. Strain gauges and accelerometers are conventionally used for structural monitoring. Recently, more advanced measurement techniques such as camera based non-contact vision sensors have been used. Another recent development is sensors being used for applications outside traditional structural monitoring. For example, vibration data has been used to detect occupancy and to infer activities on construction sites. Because of the availability of cheaper sensors and the possibility to store large amount of data on cloud, the amount of data collected has increased enormously. Interpreting and explaining the data has become a challenge. Big data analytics has become a popular research area.
This Research Topic looks at ways to analyze sensor data in the engineering domain. Data analysis involves the use of visual processing techniques, as well as statistical techniques and machine learning. The primary goal of this activity is to extract useful information from data that can be used for decision making. Papers that illustrate the use of modern techniques for data analysis are invited for publication under this Research Topic.
Relevant topics include, but are not limited to, the following:
• Image processing
• Computer vision
• Spectral analysis
• System identification
• Developing models from data
• Model-free methods
• Feedback control and automation
Keywords: Sensors, Machine learning, Data mining, Data analytics, Big Data
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.