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How an Edge-to-Cloud Data Platform Works
技术
- 分析与建模 - 边缘分析
- 平台即服务 (PaaS) - 边缘计算平台
适用功能
- 离散制造
- 流程制造
用例
- 边缘计算与边缘智能
服务
- 系统集成
挑战
在 Litmus，客户面临的最大挑战是访问他们为机器学习和分析模型提供动力所需的数据。大型制造商来到 Litmus 寻求以最快的方式连接到他们的资产并将数据发送到云。公司不仅需要将数据发送到云端以创建机器学习模型，还需要使用统一的边缘到云平台将这些模型部署回边缘。
解决方案
统一的边缘到云端数据连接平台弥合了边缘工业设备与云端大数据和机器学习系统之间的差距。该平台部署在边缘计算设备上，旨在收集数据并将其结构化为通用数据格式。统一的边缘到云平台充当数据代理，支持边缘应用和分析，以及云中的大数据和机器学习。
Litmus 被部署为工业资产旁边的边缘计算平台——从源头收集和规范化数据。即用型数据在边缘进行管理以进行本地分析，并发送到云和大数据系统以进行更复杂的处理。数据模型被部署回边缘以完成循环。
运营影响
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