SBIR Phase I: Building a Global Community to Crowdsource-Clean the Planet

SBIR 第一阶段：建立一个众包清洁地球的全球社区

• 批准号: 1746758
• 负责人: Jeff Kirschner
• 金额: $ 22.5万
• 依托单位: Litterati Inc.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-01-01 至 2018-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1746758&HistoricalAwards=false
• 关键词: SBIR; Phase; Building; Global; Community

The broader impact/commercial potential of this SBIR Phase I project stems from developing a crowdsourced solution to litter - one of the world's most pervasive and toxic problems. To many, it's dirty, disgusting, and someone else's problem to solve. Unfortunately, we all suffer the consequences, as litter impacts our economy, degrades the environment, demoralizes community pride, kills wildlife, and poisons the food system. This project aims to develop a mobile technology that empowers anyone to identify, map, and collect the world?s litter, while simultaneously connecting to a broader community of associated brands, cities, schools. By crowdsourcing the data and cleanup, there is great potential in collecting massive amounts of information which can be used for everything from infrastructure improvement, to resource allocation, brand packaging redesign, and even individual responsibility and behavioral change.The intellectual merit of this project is derived from building a global database of litter. And one critical need to achieving such a monumental task is the ability to quickly (and accurately) identify any piece of litter, anytime, anywhere even if the litter is in a deep state of decay and decomposition. This project further aims to integrate that information with other data sets including location, time, proximity to schools, and the watershed. By leveraging technologies such as image recognition and machine learning, the project will further empower the people who are crowdsourcing the data and cleanup to collect a vast amount of identifiable information.

这个SBIR第一阶段项目的更广泛的影响/商业潜力源于开发一个众包的解决方案，垃圾-世界上最普遍和有毒的问题之一。对许多人来说，这是肮脏的，恶心的，别人的问题要解决。不幸的是，我们都遭受了后果，因为垃圾影响我们的经济，恶化环境，挫伤社区自豪感，杀死野生动物，毒害食品系统。该项目旨在开发一种移动的技术，使任何人都能够识别，绘制地图和收集世界？的垃圾，同时连接到一个更广泛的社区的相关品牌，城市，学校。通过众包数据和清理，收集大量信息的潜力巨大，这些信息可以用于从基础设施改善到资源分配，品牌包装重新设计，甚至个人责任和行为改变的方方面面。这个项目的智力价值来自于建立一个全球垃圾数据库。要完成这样一项艰巨的任务，一个关键的需求是能够随时随地快速（准确）识别任何垃圾，即使垃圾处于腐烂和分解的深度状态。该项目的进一步目标是将这些信息与其他数据集结合起来，包括位置、时间、与学校的距离和流域。通过利用图像识别和机器学习等技术，该项目将进一步授权众包数据和清理人员收集大量可识别信息。