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합리적 보험료 산정을 위한 OpenCV기반 반려동물 건강나이 예측 시스템

OpenCV-Based Pets Health Age Prediction System for Reasonable Insurance Premium Calculation

  • 지민규 (동서대학교 소프트웨어학과) ;
  • 김요한 (동서대학교 소프트웨어학과) ;
  • 박승민 (동서대학교 소프트웨어학과)
  • Min-Kyu Ji ;
  • Yo-Han Kim ;
  • Seung-Min Park (Dept. Software, Dongseo University)
  • 투고 : 2024.04.25
  • 심사 : 2024.06.12
  • 발행 : 2024.06.30

초록

국내 펫 보험은 2007년 첫 도입되어 현재 2024년 지금까지 많은 보험상품들이 생겼고 펫 보험 시장은 매년 증가하고 있는 추세이다. 하지만 실상은 2022년 기준 펫 보험 가입률은 전체 반려인의 0.8%이며 반려인들은 비싼 보험료 및 보장내역, 까다로운 가입 기준으로 인해 펫 보험 가입을 꺼리고 있다. 본 논문에서는 반려동물 안구질환 및 질환의 위치를 인식하고 건강나이를 예측 가능한 모델링을 제안한다. 먼저 EfficientNet을 활용해 반려동물의 안구질환을 인식하고 OpenCV를 활용 질환의 발병 위치와 크기를 인식하여 반려동물의 건강나이를 산출한다. 산출된 해당 건강나이를 바탕으로 보험사에서 펫 보험료 산정 시 보조하는 역할을 하고자 한다. 이 모델링은 반려동물 안구질환 및 건강나이로 합리적인 펫 보험 가격 산정 보조가 가능하다.

In 2007, the first domestic pet insurance policies were introduced, and by 2023, numerous insurance products had been developed. The pet insurance market has been expanding steadily. However, as of 2022, only 0.8% of all pet owners have subscribed to pet insurance. Pet owners hesitate to enroll in pet insurance due to expensive premiums, unclear coverage details, and strict enrollment criteria. This paper proposes a model capable of detecting pet eye diseases and predicting their health age. Initially, EfficientNet is employed to identify the pet's eye disease, while OpenCV is utilized to locate and measure the size of the disease, enabling the calculation of the pet's healthy age. By leveraging the calculated health age, the aim is to aid insurance companies in determining pet insurance premiums. This model can facilitate the calculation of reasonable pet insurance rates based on the pet's eye condition and health age. Ultimately, the objective is to implement a system capable of detecting pet eye conditions and predicting their health age.

키워드

과제정보

이 논문은 2023년도 동서대학교 "Dongseo Cluster Project" 지원에 의하여 이루어진 것임. (DSU-20230005)

참고문헌

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