Skip to content
Back Home
  • About
    • The mission
    • Contacts
    • People who are involved
    • External Advisory Board
  • News
  • Events
    • 10th SmartData@PoliTO Workshop – Present and Future Directions
    • 9th SmartData@PoliTO Workshop – SmartData@PoliTO meets AI-H@PoliTO
    • La biblioteca nel metaverso – la Reading & Machine
  • Workshops
    • Seminars
      • AI4Industry – the role of AI and Data-driven Analysis in the Future of European Industry
      • On the dynamics of music virality and its relation with mainstream success
      • Bypass frauds in cellular networks: from Financial strikes to Data poisoning
    • SmartTalks
  • Education
    • Courses for PhD students
    • PhD Course: Topological Data Analysis
    • PhD Course: Data Science for Networks
    • Corporate training on Digital Transformation
  • Research
    • Publications
    • Current PhD
    • Projects
    • Open Datasets & Libraries
    • Topics
  • Open Positions
    • open position – PhD student
    • open position – Assistant Professor with time contract (RTD-A)
    • open position – PostDoc researchers
    • Open position – Technologist
  • BigData Cluster
    • Computing Facilities
    • Request BigData@Polito Account
    • BigData@Polito Access Instructions
    • Run Jobs with Custom Packages
  • Private Area
  • Search
Back Home
  • About
    • The mission
    • Contacts
    • People who are involved
    • External Advisory Board
  • News
  • Events
    • 10th SmartData@PoliTO Workshop – Present and Future Directions
    • 9th SmartData@PoliTO Workshop – SmartData@PoliTO meets AI-H@PoliTO
    • La biblioteca nel metaverso – la Reading & Machine
  • Workshops
    • Seminars
      • AI4Industry – the role of AI and Data-driven Analysis in the Future of European Industry
      • On the dynamics of music virality and its relation with mainstream success
      • Bypass frauds in cellular networks: from Financial strikes to Data poisoning
    • SmartTalks
  • Education
    • Courses for PhD students
    • PhD Course: Topological Data Analysis
    • PhD Course: Data Science for Networks
    • Corporate training on Digital Transformation
  • Research
    • Publications
    • Current PhD
    • Projects
    • Open Datasets & Libraries
    • Topics
  • Open Positions
    • open position – PhD student
    • open position – Assistant Professor with time contract (RTD-A)
    • open position – PostDoc researchers
    • Open position – Technologist
  • BigData Cluster
    • Computing Facilities
    • Request BigData@Polito Account
    • BigData@Polito Access Instructions
    • Run Jobs with Custom Packages
  • Private Area
Home » Publications » PREMISES, a scalable data-driven service to predict alarms in slowly-degrading multi-cycle industrial processes

PREMISES, a scalable data-driven service to predict alarms in slowly-degrading multi-cycle industrial processes

Stefano Proto, Francesco Ventura, Daniele Apiletti, Tania Cerquitelli, Elena Maria Baralis, Enrico Macii, Alberto Macii (2019) PREMISES, a scalable data-driven service to predict alarms in slowly-degrading multi-cycle industrial processes, In: 2019 IEEE International Congress on Big Data, pp. 139-143, ISBN: 978-1-7281-2772-9

Post navigation

  • Previous post Towards a real-time unsupervised estimation of predictive model degradation
  • Back to post list
  • Next post Eurecom-Polito at TRECVID 2017: Hyperlinking task

Collaborations

 

© 2025 SmartData@PoliTO – All rights reserved

Homepage - Privacy - Cookie Policy - Contacts