AI notification is an artificial intelligence-based notification service for drivers with cars. Various schedules can be stored in the form of a calendar, and it has the function of deriving the expected departure time by entering the departure place, arrival place, and arrival time. Currently, future traffic prediction technology can predict up to 6 hours later, so if you have a schedule after 6 hours, you can get an alarm in the form of a pop-up, tell you the meeting place, arrival time, estimated departure time, and 10 minutes before departure.
AI notifications are equipped with a business card storage function, so when you take a picture of your business card, it is automatically saved in your business card house, making it convenient to manage your business card. Additionally, you can search through the search function. It also calculates the time it takes to park through parking status data and linkage.
When parking is completed through AI notification, it automatically saves the parked location and guides you through the route of the parked location from the current location when you run the AI notification application in the future. AI notifications can be linked to traffic control systems and butterfly boxes through future speed prediction technology, and various traffic information can be delivered in real time to provide more accurate traffic prediction and expected time required.
How to apply AI data processing - Data collection and classification AI automation
Standardization of Traffic Data - AI Automatic Classification Technology
- Automation technology for column classification through traffic data collection and EDA search standardization
- Normal expression-based standardization technology based on image processing (recognition, counting, labeling, etc.)
- Traffic data collection cycle optimization technology reflecting traffic flow
AI Schedule with Artificial Intelligence-based Future
Traffic Condition Prediction PlatformRoad Traffic Prediction System Extension Parking
Information Interworking Technology
In addition, machine learning-based urban road speed prediction traffic information provision service
- Multi-level k-nearest neighbors-based speed prediction for local roads subject to signal control.
- Development of a data preprocessing function for roads in the target area.
- Development of a road-specific prediction algorithm that searches for and weighted averages road traffic speed data through past historical data pattern matching
where real-time data and traffic patterns are most similar [Figure 12]
- Establishment and visualization of prediction-related information DB for linkage with signal control algorithms and GUI.
- It is a speed prediction traffic information service that provides prediction accuracy and speed improvement information by exploring traffic patterns considering the characteristics
of each stage (by day, road network, road link unique).