18204750. SERVICE OPTIMIZATION SYSTEM, SERVICE OPTIMIZATION METHOD, AND NON-TRANSITORY COMPUTER-READABLE STORAGE MEDIUM simplified abstract (TOYOTA JIDOSHA KABUSHIKI KAISHA)

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SERVICE OPTIMIZATION SYSTEM, SERVICE OPTIMIZATION METHOD, AND NON-TRANSITORY COMPUTER-READABLE STORAGE MEDIUM

Organization Name

TOYOTA JIDOSHA KABUSHIKI KAISHA

Inventor(s)

Tomoyuki Kaga of Mishima-shi (JP)

Hideo Hasegawa of Nagoya-shi (JP)

Hiroya Matsubayashi of Koto-ku (JP)

Yuki Ichioka of Kawasaki-shi (JP)

Nobuhisa Otsuki of Toyota-shi (JP)

SERVICE OPTIMIZATION SYSTEM, SERVICE OPTIMIZATION METHOD, AND NON-TRANSITORY COMPUTER-READABLE STORAGE MEDIUM - A simplified explanation of the abstract

This abstract first appeared for US patent application 18204750 titled 'SERVICE OPTIMIZATION SYSTEM, SERVICE OPTIMIZATION METHOD, AND NON-TRANSITORY COMPUTER-READABLE STORAGE MEDIUM

Simplified Explanation

The service optimization system uses simulation to predict the demand for a service based on real data of a customer's behavior, behavior history, and behavior schedule related to the service. It also uses a service model to determine the setting value of a service parameter for maintaining the level of the service based on the predicted demand. The system then acquires real data after the service is provided using the determined setting value of the service parameter to feed back into the simulation using the human model.

  • The system predicts service demand based on customer behavior data.
  • It determines the setting value of a service parameter to maintain the service level.
  • Real data is acquired and fed back into the simulation using the human model.

Potential applications of this technology:

  • Service optimization and resource allocation in industries such as healthcare, transportation, and hospitality.
  • Predictive analysis for demand forecasting and capacity planning in service-based businesses.

Problems solved by this technology:

  • Inefficient resource allocation due to inaccurate demand forecasting.
  • Inability to maintain service levels based on changing demand patterns.
  • Lack of insights into customer behavior and its impact on service utilization.

Benefits of this technology:

  • Improved efficiency and cost-effectiveness in service delivery.
  • Enhanced customer satisfaction through optimized service levels.
  • Better decision-making based on accurate demand predictions and behavior analysis.


Original Abstract Submitted

The service optimization system performs simulation using a human model modeling service utilization behavior of a customer to predict a demand for a service from real data including at least one of behavior, behavior history, and behavior schedule of the customer related to the service. Also, the service optimization system performs simulation using a service model modeling a relationship between a service parameter determining content of the service, a demand for the service, and a level of the service to determine a setting value of the service parameter for maintaining the level of the service based on the predicted demand. Then, the service optimization system acquires the real data after the service is provided using the determined setting value of the service parameter to feed back the acquired real data to an input of the simulation using the human model.