Bltn AI协作平台

设计师： Chiwon Lee

客户: Multitude Insights

软件类别A' Design Award 铜奖获奖者

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关于 Bltn AI协作平台

BLTN是一个软件即服务（SaaS）平台，集成了自然语言处理技术（NLP）和人工智能（AI），用于简化政府科技（GovTech）领域的公共安全工作。BLTN为执法人员简化了数据录入和共享流程，确保操作流畅无间。其先进的搜索功能运用复杂算法，实现高效的案件识别。人工智能技术的融入显著提升了案件侦破的速度与准确性。BLTN秉持实用与功能并重的设计理念，提供简明直接的解决方案，成为执法机构的宝贵资产。

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关于A' Design Award 铜奖

Bltn AI协作平台是 A' Design Award 铜奖得主，这是授予以创造力、独创性和敏锐见长的杰出设计的极具声望的认可。铜奖得主是技艺娴熟、创意惊人的作品，印证了其设计师丰富的经验、想象力与机智。预计Bltn AI协作平台将成为一件备受推崇、令人钦佩且被珍爱的物品，兼具显著的专业性与创新性。这件赢得 A' Design Award 铜奖的设计融入艺术、科学、设计和技术领域的最佳实践，并因注重细节而出类拔萃。Bltn AI协作平台出色地满足需求，触动渴望，迷住情感，并吸引好奇心。

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由设计师提供的致谢、团队成员及技术详情。

独特属性: 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.
尺寸与包装: 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.
标签: Artificial Intelligence, Natural Language Processing, Public Safety, Collaboration, Information Sharing, Digital Infrastructure, Civic Technology, Crime Reduction
生产技术: 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.
设计挑战: 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.
研究: 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.
灵感: 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.
项目周期: 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.
操作流程: 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.
团队成员: Chiwon Lee
Yeun Soo (Lauren) Choi
Minjung Kim
Seongbin Lee
Seowon Park