人工智能公司在 3 个月内绘制国家比例地图：案例研究
技术
- 无人机 - 无人机飞行与导航软件
- 基础设施即服务 (IaaS) - 云计算
适用行业
- 建筑物
- 海洋与航运
适用功能
- 质量保证
用例
- 运动预测
- 智能照明
服务
- 系统集成
- 测试与认证
关于客户
该客户是一家领先的人工智能云计算公司，需要定制、经济高效的地图解决方案。他们需要一种能够在短短三个月内有效绘制整个阿联酋地图的解决方案。该公司需要一个具有自定义地图数据属性的大规模端到端解决方案。他们还需要地图数据能够轻松地与现有的路线和导航引擎集成。该公司正在寻找一种解决方案，可以轻松地与其下游路由和导航引擎集成，生成可以在地图解决方案提供商提供很少/没有帮助的情况下轻松使用的地图数据，并遵循标准模式和标记结构以及提供的定制规范被他们。
挑战
一家领先的人工智能云计算公司面临着在三个月内为整个阿联酋创建大规模端到端地图解决方案的挑战。该公司需要以快速刷新率构建高精度、国家范围的地图，这是一项既昂贵又广泛的任务。该过程涉及在阿联酋级别构建地图、添加 50 多个自定义属性、执行质量检查和冲突解决，以及不断维护和刷新地图数据。该公司还需要从多个图像源获取地图数据情报，这是一个耗时的过程。不同的路由和导航引擎（例如 OSRM 等）使用的数据结构因路由引擎类型而异。客户需要能够轻松与其现有路线和导航引擎集成的地图数据。
解决方案
该解决方案采用了一种将人工智能与地图专业知识相结合的专门方法。建立了一个平台，将专有图像数据覆盖在集成地图编辑平台中。该平台能够合并和对齐专有街道级图像、私有图像和开源图像，集成客户的专有图像数据，将派生的数据智能合并到一个地图堆栈中，并遵循客户内部路线和导航的模式和标记结构引擎。人工智能模块用于有效地从街道和卫星图像中提取地图属性。利用任务分配平台来利用现有的 OpenStreetMap (OSM) 模式来降低成本并缩短周转时间。构建了自定义 QA 工具来对属性执行严格的平台检查，以确保高质量。
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