디자이너 Chiwon Lee의 작품 Bltn AI 협업 플랫폼은(는) 매우 권위 있는 2024 A' Design Award 동상의 소프트웨어 디자인 부문에서 탁월한 수상작입니다.

동소프트웨어· 2024

Bltn AI 협업 플랫폼

디자이너: Chiwon Lee

클라이언트: Multitude Insights

소프트웨어 부문 A' Design Award 동상 수상작

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Bltn AI 협업 플랫폼 소개

BLTN은 자연어 처리 기술(NLP)과 인공지능(AI)을 통합하여 정부 기술(GovTech) 분야의 공공 안전 활동을 간소화하는 서비스형 소프트웨어(SaaS) 플랫폼입니다. BLTN은 법 집행 기관 담당자들의 데이터 입력 및 공유를 간소화하여 원활한 운영을 보장합니다. 고도화된 검색 기능은 복잡한 알고리즘을 활용하여 효율적인 사례 식별을 가능하게 합니다. AI의 통합은 범죄 해결 속도와 정확성을 향상시킵니다. BLTN의 실용적이고 기능적인 디자인은 직관적인 솔루션을 제공하여 법 집행 기관에 귀중한 자산이 됩니다.

수상 인정

A' Design Award 동상 소개

Bltn AI 협업 플랫폼, 이 작품은 A' Design Award 동상 수상작으로, 창의성, 독창성, 영민함으로 돋보이는 뛰어난 디자인에 수여되는 높은 권위의 인정입니다. 동상 수상작은 충분히 숙련되고 인상적으로 창의적인 작품으로, 디자이너의 폭넓은 경험, 상상력, 기지를 입증합니다. Bltn AI 협업 플랫폼, 이 작품은 높이 평가받고 감탄과 사랑을 받는 사물로서 두드러지게 전문적이고 혁신적일 것으로 기대됩니다. 이 동상 수상 디자인은 예술, 과학, 디자인, 기술의 모범 사례를 담고 있으며 세부에 대한 주의로 훌륭합니다. Bltn AI 협업 플랫폼, 이 작품은 필요를 훌륭하게 충족하고 욕망에 닿으며 감정을 매료하고 호기심을 불러일으킵니다.

디자인 비하인드

프레스 킷

디자이너가 제공한 크레딧, 팀원 및 기술 세부 사항.

고유 특성: BLTN is an AI-powered information-sharing platform for police officers. As officers upload crime data into BLTN, the AI looks for connections between them and intelligently alerts users. BLTN uses NLP and object recognition to look for clues that can unlock a case, especially for crimes that span multiple jurisdictions. Then, users connect through on-platform messaging and collaborative analysis tools. BLTN has successfully solved burglary, gang, and missing child cases across the U.S.
치수 및 패키징: Web dimensions are 1440 px * 1024 px. BLTN is a B2G SaaS product available on the Web and Mobile that is FBI CJIS certified. It is only available to licensed and authorized individuals in the law enforcement space.
태그: Artificial Intelligence, Natural Language Processing, Public Safety, Collaboration, Information Sharing, Digital Infrastructure, Civic Technology, Crime Reduction
생산 기술: The platform is hosted on AWS and powered by NLP and AI. The NLP aids the search feature and the AI enables the recommendation and detection feature. An advanced Geographic Information System (GIS) technology is employed to enable the geo-visualization of crime data. The design was primarily carried out in Figma by using a design system and informed by quantitative and qualitative research with real users. The qualitative research was analyzed via open coding and affinity diagramming.
디자인 과제: The challenge is that BLTN is addressing a data heavy and complex space that requires advanced levels of security and visibility controls due to the nature of the law enforcement industry. BLTN also has a variety of features powered by advanced technology that need to be compatible with each other. It was challenging to ensure the data is easy to consume, easy to navigate, and easy to share while also applying technological advances to aid the users in the law enforcement space.
연구: Qualitative research was conducted on law enforcement officers that are users of BLTN with the objective of understanding user pain points and user needs. Semi-structured interviews and task analysis was conducted via online conferencing tools. The research data was analyzed through open coding and affinity diagramming. The software version with user insights applied has been selected as the central communications platform for the High Intensity Drug Trafficking Area (HIDTA) program.
영감: More than 50% of crimes in the United States remain unsolved. This is primarily because very few inter-agency data sharing initiatives exist, so criminals can easily move between jurisdictions. Further, it is difficult to upload and share data as existing platforms require manual entry. Because of these disconnected and manual systems, detecting trends and connections between crimes is an incredibly complex problem given the size and scope of data uploaded daily.
프로젝트 기간: BLTN was published in May, 2022, and the design project for refining BLTN started in May, 2023 and finished in September, 2023 in the United States.
운영 흐름: Police users log in and can view posts from other users and agencies in their area. They can view these in a grid or geo-referenced manner. As officers post, an AI scans all media, text, and unstructured data for connections. Users are alerted to relevant links and put in contact with the relevant agencies/users via on-platform messaging. Users can link data through link controls and visualize linkages on the map or evidence board views helping to solve the crime.
팀원: Chiwon Lee
Yeun Soo (Lauren) Choi
Minjung Kim
Seongbin Lee
Seowon Park