FETC International's Innovative Approach: Building a connected Smart Highway System with Weather, Equipment Lifetime, and Historical Lightning Data Integration
In the rapidly evolving landscape of smart infrastructure, FETC International has taken a groundbreaking step towards enhancing highway systems by incorporating a diverse range of data sources. Through the integration of weather data, equipment lifetime analytics, and historical lightning data, FETC International is revolutionizing the way we perceive and manage our highways. This innovative approach aims to improve safety, optimize maintenance practices, and enhance overall efficiency in transportation networks.
By analyzing equipment usage and performance data, the system predicts maintenance needs and schedules repairs before failures occur. This reduces downtime, minimizes traffic disruptions, and extends the highway infrastructure's lifespan.
Provide level of risks in the occasion of thunderstorm and heavy rains 45 minutes ahead in order to ensure the safety of maintenance personnel.
Providing on-site weather forecast data through an API for real-time integration with a Dashboard monitoring system, serving as a reference for weather-related decision-making and other innovative applications.
FETC International's integration of real-time weather data, equipment lifetime analytics, and historical lightning data marks a significant leap forward in the development of smart highway systems. This innovative approach not only enhances safety and efficiency but also demonstrates the potential of data-driven solutions in shaping the future of transportation infrastructure.
As technology continues to advance, the integration of diverse data sources is likely to play a pivotal role in creating resilient, adaptive, and sustainable smart highway systems that benefit communities around the world.
Paired with self-built sensing stations, it simultaneously detects in-cloud lightning and cloud-to-ground lightning, providing lightning warnings for the next 45 minutes.
The AI Weather Prediction Module is trained using meteorological data from the Public IoT for Civil IoT Taiwan Services and data from self-built sensing stations, effectively providing localized weather forecasts.