@article{1360293,
      recid = {1360293},
      author = {Balali, Farhad. and Nouri, Jessie. and Nasiri, Adel. and  Zhao, Tian.},
      title = {Data Intensive Industrial Asset Management : IoT-based  Algorithms and Implementation /},
      publisher = {Springer International Publishing,},
      address = {Cham :},
      pages = {1 online resource (XXI, 236 pages 132 illustrations, 126  illustrations in color.) :},
      year = {2020},
      abstract = {This book presents a step by step Asset Health Management  Optimization Approach Using Internet of Things (IoT). The  authors provide a comprehensive study which includes the  descriptive, diagnostic, predictive, and prescriptive  analysis in detail. The presentation focuses on the  challenges of the parameter selection, statistical data  analysis, predictive algorithms, big data storage and  selection, data pattern recognition, machine learning  techniques, asset failure distribution estimation,  reliability and availability enhancement, condition based  maintenance policy, failure detection, data driven  optimization algorithm, and a multi-objective optimization  approach, all of which can significantly enhance the  reliability and availability of the system. Provides a  comprehensive reference, focused on the Asset Health  Management Optimization Approach Using Internet of Things  (IoT); Describes a data-driven optimization method, which  considers the challenges raise by big data analysis;  Enables a multi-objective approach, which includes the  healthy index, reliability, availability, and cost, with  respect to the optimization methods and computational  restrictions which can have various applications.},
      url = {http://library.usi.edu/record/1360293},
}