Safe-T Teen Driver Safety Application

Description:

Safe-T improves the driving habits of teenagers aged 14-18 through real-time data analytics, AI behavioral analysis, and personalized feedback using smartphone sensors, vehicle telemetry, and cloud processing. It identifies risky driving patterns early, delivers corrective alerts, and engages teens with interactive learning and gamified challenges while prioritizing data privacy and security.

 

Key Advantages:

  • Real-time AI-driven detection and alerts of risky driving behaviors.
  • Personalized feedback and interactive learning modules to promote safe habits.
  • Scalable solution requiring no specialized hardware.
  • Modular, adaptable architecture enabling integration with smart vehicle systems.
  • Comprehensive data privacy and security compliant with GDPR and CCPA.
  • Multi-layered warning system using audio, visual, and haptic notifications.

 

Problems Solved:

  • High incidence of unsafe driving behaviors among teenage drivers.
  • Lack of immediate, actionable feedback to correct risky driving in teens.
  • Limited engagement tools that effectively promote safe driving habits.
  • Privacy concerns related to driver data collection and sharing.
  • Challenges in integrating safety technologies with existing vehicle systems.

 

Market Applications:

  • Teen driver education programs and parental monitoring.
  • Insurance companies offering risk-based incentives and discounts.
  • Automotive manufacturers integrating driver safety features.
  • Schools and driver training organizations.
  • Fleet operators with young or novice drivers.

 

Patent Information:
Title App Type Country Serial No. Patent No. File Date Issued Date Expire Date Patent Status
Safe-T: Road Safety Application for Teen Drivers Provisional United States 63/776,074   3/22/2025   3/23/2026 Pending
Category(s):
Data/AI
Engineering
For Information, Contact:
Robert Reis
Licensing Associate
Texas State University - San Marcos
svj24@txstate.edu
Inventors:
Anandi Dutta
Anannya Tusti
Subasish Das
Keywords:
AI-Driven Behavioral Analytics
Automotive Safety Technology
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