DMIS 2017 - 2017 Workshop on Data Mining for Industrial Safety

Industrial safety is important for safeguarding people’s life, especially in high risk domains such as nuclear, aircraft, chemical, oil and mining, and transportation industry. In these domains, a small misoperation may be catastrophic. Industrial safety tries to reduce the threat from these high risk domains to people. As various sensors have been widely deployed into industrial equipment, it enables to achieve a feasible scheme by mining the data from these sensors. Such a scheme is better than the traditional, because it is based on mining the special data from a potential risk source, and by such mining, the features of this potential risk can be obtained. With these features to design the algorithms/methods/schemes for industrial safety, the performance of the designed algorithms/methods/schemes will be better, because of the high pertinence between a solution and the corresponding problem.
The target of industrial safety is to maintain a safe and healthy environment by designing different algorithms/methods/schemes for different industrial problems, for example, time series model based prediction algorithms are designed to predict the location and time point of a potential safety risk by mining the time series data from industrial environment.