AI Predicts Drowsiness! ad-dice Invites Companies to Participate in the "Drowsiness Score" Trial

TAITO-KU, Japan - Nov. 29, 2024 - PRLog -- ad-dice, Co., Ltd. (CEO: Daisuke Ito / Head office: Taito City, Tokyo) announced a trial of its new "Drowsiness Score" in the healthcare AI ResQ AI, starting Tuesday, October 8, 2024.

The "Drowsiness Score," based on ad-dice's proprietary "SoLoMoN* Technology" platform, supports field worker health monitoring and promotes safe operations.
*Register edas a trademark in Japan.

1. Application Guidelines
Target Industries: Transportation (buses, taxis, trucks, airplanes, ships), warehousing, and other businesses requiring measures against employee drowsiness.

• Application Deadline: By 23:59, Friday, December 20, 2024 (JST).
• Trial Period: Up to 60 days from the start (negotiable). Ends Friday, January 31, 2025.
• Cost: Free (subject to customer consultation). Customers may bear some costs (e.g., communication). *Each person will need a smartphone to link smartwatch data to ResQ AI. A PC and a browser are required to access and use ResQ AI.
• How to Apply: Submit the form here (https://forms.gle/K7agxy5JXSzwHk7WA). Meetings will follow applications.

2. Trial Flow
1. Employees wear a smartwatch.
2. Vital data (e.g., heart rate, respiratory rate) is sent to ResQ AI via smartphone.
3. ResQ AI analyzes the physical and mental state of the employee and presents the current and predicted values of the "Drowsiness Score".

3. Case Studies
ad-dice has partnered with a sightseeing bus company and a non-life insurance company to test the "Drowsiness Score" in preventing drowsy driving.
Details: February 29, 2024, Press Release
"AI Prevents Traffic Accidents Caused by Drowsy Driving by Drivers and Crew Members"
Bus company, non-life insurance company, and AI platform developer start demonstration experiment to build a new AI to predict drowsiness with ad-dice's health monitoring AI "ResQ AI"."
https://prtimes.jp/main/html/rd/p/000000026.000056652.html

4. Background
Labor shortages, aging workforces, and capped driver hours in Japan's transport industry pose challenges.

In the U.S., the Three Mile Island nuclear accident (1979) highlighted the dangers of human error caused by fatigue. Similarly, the Challenger explosion (1986) and Chernobyl disaster (1986) also stemmed from sleep deprivation and operational errors.

Proactively addressing workplace fatigue is essential to prevent accidents. Using its proprietary "SoLoMoN Technology" (Patent No. 6302954), ad-dice offers AI solutions that analyze IoT data to predict and score risk signs.

The "Drowsiness Score" analyzes vital data to predict drowsiness, alerting drivers and managers before risks escalate. Unlike conventional methods, it issues warnings based on predictive risk scores, ensuring safer operations and reducing drowsiness-related accidents.