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Starts 4 July 2025 17:52

Ends 4 July 2025

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Boosting Infrastructure Safety with Mobile Edge AIoT

Explore a comprehensive guide on how to implement data-driven maintenance strategies that elevate the safety and efficiency of infrastructure systems. Whether it's roads, highways, or railways, learn how Mobile Edge AIoT can revolutionize maintenance solutions, fostering safer environments and streamlined operations. Explore the integrat.
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Overview

Explore a comprehensive guide on how to implement data-driven maintenance strategies that elevate the safety and efficiency of infrastructure systems. Whether it's roads, highways, or railways, learn how Mobile Edge AIoT can revolutionize maintenance solutions, fostering safer environments and streamlined operations.

  • Explore the integration of Mobile Edge AIoT in infrastructure safety.
  • Uncover methods that lead to enhanced operational efficiency.
  • Gain insights into practical applications for road, highway, and rail networks.

Ideal for professionals seeking to advance in the fields of artificial intelligence and computer science, this course is brought to you by industry leader YouTube, known for delivering the latest in technological advancements.

Syllabus

  • Introduction to AIoT and Mobile Edge Computing
  • Overview of AIoT and its applications in infrastructure
    Fundamentals of mobile edge computing
    Benefits of integrating AIoT with edge computing
  • Understanding Infrastructure Safety Challenges
  • Common safety issues in road, highway, and rail systems
    The role of data in identifying and addressing safety concerns
    Case studies of safety incidents and lessons learned
  • Data Collection and Sensor Technologies
  • Types of sensors used in infrastructure monitoring
    Data collection methods for infrastructure health assessment
    Real-time data processing at the edge
  • Building AI Models for Predictive Maintenance
  • Introduction to predictive maintenance concepts
    Developing AI models for fault detection and prevention
    Training, validating, and deploying edge AI models
  • Implementing Mobile Edge AIoT Solutions
  • Designing an AIoT infrastructure safety system
    Selecting hardware and software components
    Integration of edge devices with central systems
  • Enhancing Operational Efficiency
  • Automating routine maintenance tasks using AIoT
    Real-time decision-making with edge analytics
    Cost-benefit analysis of AIoT solutions in infrastructure
  • Safety Regulations and Compliance
  • Understanding regulatory requirements for infrastructure safety
    Ensuring AIoT systems comply with safety standards
    Strategies for managing data privacy and security
  • Case Studies and Real-World Applications
  • Successful implementation of AIoT in road, highway, and rail safety
    Lessons learned from existing projects
    Future trends and innovations in AIoT infrastructure safety
  • Final Project
  • Designing a comprehensive AIoT safety solution for a specific infrastructure
    Presentation and peer review of project solutions.

Subjects

Computer Science