Knowledge Capsule 流動應用程式 by Baidu Online Network Technology Beijing

Knowledge Capsule 流動應用程式 by Baidu Online Network Technology Beijing is a highly esteemed winner of the very prestigious 2023 A' Design Award 銅獎 in 流動設計 Competition Category.

銅流動· 2023

Knowledge Capsule 流動應用程式

by Baidu Online Network Technology Beijing

Client: Baidu Online Network Technology. Beijing

A' Design Award 銅獎 Winner in 流動 Category

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Verified Award Winner

Verify Award Status for #148150

View at A' Design Award Press Release Award Badge

Colors

The Design

About Knowledge Capsule 流動應用程式

知識膠囊係一款專注於心理健康教育嘅流動應用程式。知識膠囊精選咗一啲大約三分鐘嘅短片，解說各種心理輔導主題。人工智能會為內容加上標籤，再經過人工審核以確保質素。系統會根據每位用戶嘅觀看記錄同個人檔案，向佢哋推薦合適嘅內容。一個擬人化嘅助手會引導成個互動過程，令體驗更加輕鬆自在。虛擬課堂俾用戶可以學習之餘，仲可以同其他人比較學習進度。呢個設計嘅目標，係令心理健康知識變得簡單易明。

The Recognition

About the A' Design Award 銅獎

Knowledge Capsule 流動應用程式是 A' Design Award 銅獎得主，這是授予以創造力、獨創性和敏銳見長的傑出設計的極具聲望的認可。銅獎得主是技藝嫻熟、創意驚人的作品，印證了其設計師豐富的經驗、想像力與機智。預計Knowledge Capsule 流動應用程式將成為一件備受推崇、令人欽佩且被珍愛的物品，兼具顯著的專業性與創新性。這件贏得 A' Design Award 銅獎的設計融入藝術、科學、設計和技術領域的最佳實踐，並因注重細節而出類拔萃。Knowledge Capsule 流動應用程式出色地滿足需求，觸動渴望，迷住情感，並吸引好奇心。

Behind the Design

Press Kit

Credits, team members and technical details provided by the designer.

Unique Properties: For different psychological problems, Knowledge Capsules selects the relevant mental health content through big data and presents users with 3 minutes short videos, accurately related to the diagnosis and treatment contents of users, based on AI technology. This product makes complex mental health knowledge lively and interesting with, helping users face up to and recognize themselves scientifically.
Tags: AI psychological counseling, Depression, Mental health
Production Technology: Tag content resources: dual form of manual and AI. AI recognizes video content, extracts keyword, classifies relevant content, and then with manual review to ensure high quality content, greatly reducing labor costs.
Intelligent content push: Based on the content type and viewing duration of previous consumption, AI recommends content that similar users are interested in, and adjusts it in real time according to the actual consumption behaviors.
Design Challenge: Comparing psychological counseling knowledge to capsules, this product pushes accurate content to users intelligently and naturally to popularize mental health knowledge and let users pay attention to mental health problems. Anthropomorphic AI diagnosis and treatment assistant helps to narrow the distance with patients to be close. The learning process of virtual class is easy and comfortable. Users can compete with others to learn together while learning.
Research: Based on huge content ecology of Baidu and gathering experts in the psychological and other fields, this product selects 3 minutes short video through big data, which contain psychological counseling content. Users can receive diagnosis content push through AI technology accurately based on their profiles. Knowledge Capsules helps to spread mental health knowledge by making it lively and interesting and helps users make scientific interventions for mental health problems.
Inspiration: According to data released by the World Health Organization, about 1 billion people world wide suffer from mental health problems, yet mental health is one of the most neglected areas of public health. Most people may have psychological problems at different ages, which seriously affect their daily life, study and work. We need more professionals to scientifically intervene the mental and emotional world of patients with mental illness and carry out targeted treatment.
Project Duration: Developed in Beijing in November 2021 and launched on 20 February 2021.
Operation Flow: Capsule anthropomorphic design creates a relaxed and pleasant interactive experience for users with interaction and dialogue with AI diagnosis and treatment assistant;
In the era of information explosion, this product avoids complex information screening process for users with intelligent and precise content push based on their profiles.
The virtual lessons put fun in learning and supports the learning competition with other users, stimulating the learning enthusiasm.
Team Members: Yuan Lu
Xiaoli Ping
Yujie Shi
Xiaowan Li
Yong Zhang
Xin Hu
Lu Han
Shi Ouyang
Xingyu Gu
Hao Li
Jiali Ma
Yuqin Gan