SBIR Phase I: Development of Geolocation Name System (GNS)

这个SBIR第一阶段项目的重点是使地理位置直接、容易记忆和明确。消除歧义是自动化的关键部分，可以简化自治世界的基础设施。我们的目标是提供一种可移植的、用户友好的、人类可读的方法，而不是通过搜索地址来获得地理位置。在这个新的移动世界里，地理位置正变得越来越重要，它对于到达一个企业、接一个乘客、递送一个包裹或接送一个学生已经至关重要。随着自动驾驶汽车、机器人和无人机的广泛使用，地理位置将变得更加重要。具有上下文数据的地理位置信息可以成为强大的分析和可编程解决方案的基础。利用这些记录进行数据分析，可以在疾病传播、备灾、应急响应、人口流动和纵向学生分析等情况下取得非凡的成果，从而大大节省健康和灾难恢复方面的开支，并提高教育投资的效率。该项目的目标是建立一个开放的、动态的、可个性化的地理位置存储库，作为下一代地理定位应用程序（包括自主和物联网（IoT）相关解决方案）的基础，其输出可用于预测健康、天气、人口增长和/或传播的数据分析模型。地理位置存储库和管理工具可以为信息添加交互性，具有地理位置更新、近实时跟踪和数据通知的功能，并具有开发可编程解决方案的潜力。通过在存储库层之上添加具有适当功能和命令的软件应用程序编程接口，地理位置数据可以为日常应用程序提供动力，以保持数据的新鲜度，同时用于推进数据分析。在具有强大授权机制的边缘端点上提供信息时，可以将信息绑定到Internet域、电子邮件或电话，以便跨操作系统、设备和应用程序进行可移植性。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This SBIR Phase I project focuses on making geolocations direct, easy to remember, and unambiguous. Disambiguation is a critical part of automation and simplifies infrastructure for the autonomous world. Instead of searching for an address to obtain a geolocation, the goal is to provide a portable, user-friendly, human-readable method. Geolocations are becoming more important in this new mobile world and are already critical for reaching a business, picking up a passenger, delivering a package, or transporting a student. Geolocations will become even more important with the expanding use of autonomous vehicles, robots, and drones. Geolocation information with contextual data can be the foundation for powerful analyses and programmable solutions. Data analytics with these records can provide extraordinary results in scenarios of disease propagation, disaster preparedness, emergency response, population movement, and longitudinal student analysis, which can result in substantial savings on health and disaster recovery and more efficient investment in education. The goal of this project is to build an open, dynamic, personalizable geolocation repository that serves as the foundation for the next generation of geolocation- enabled applications, including autonomous and Internet-of-Things (IoT)-related solutions, and the output of which can be used in data analytic models for forecasting health, weather, and population growth and/or spread. Geolocation repository and management tools can add interactivity to the information, with capabilities for geolocation updates, near-real-time tracking, and data notifications and the potential to enable the development of programmable solutions. By adding software application programming interfaces above the repository layer with appropriate functions and commands, the geolocation data can power everyday applications to maintain data freshness while being used to advance data analytics. When provided at edge endpoints with strong authorization mechanisms, the information can be bound to Internet domains, emails, or telephones for portability across operating systems, devices, and apps.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.