项目来源

国家重点研发计划(NKRD)

项目主持人

罗军舟

项目受资助机构

东南大学

项目编号

2017YFB1003000

立项年度

2017

立项时间

未公开

研究期限

未知 / 未知

项目级别

国家级

受资助金额

1816.00万元

学科

云计算和大数据

学科代码

未公开

基金类别

“云计算和大数据”重点专项

工业互联网 ; 非传感器感知 ; 多媒体信息自适应感知 ; 自适应互联 ; 工业大数据处理与反馈控制 ; 工业互联网平台与应用示范 ; Industrial Internet ; Sensorless sensing ; Adaptive multimedia sensing ; Adaptive interconnection ; Industrial big data processing and feedback control ; Industrial Internet platform and application demonstration

参与者

何源；张兰；刘亮；孙茂杰

参与机构

清华大学；中国科学技术大学；北京邮电大学；江苏金恒信息科技股份有限公司

项目标书摘要：本项目以研发“智感、效联、迅知、协控”的云端协作关键技术、构建人机物融合的工业互联网平台为目标，围绕工业互联网体系结构、关键技术、平台与应用示范开展研究工作。在工业互联网体系结构方面，研究了工业互联网云端融合框架、基于边缘计算的云端融合协同存储机制、云端融合模型和形式化描述方法等技术，设计了云端融合、共享智能的体系结构；在非传感器感知和多媒体信息自适应感知方面，研究了商业Wi-Fi的环境下“人、机、环境”的识别、基于无线多跳网络的视频自适应监控等技术，解决了对现有传感技术感知范围有限、维度单一，多媒体信息获取方式相对固定、感知数据冗余等问题；在高效安全自适应互联技术方面，从设备层、数据层、服务层出发，研究工业互联网终端高效互联技术，以实现端与端、云与端之间安全实时通信，解决当前工业云和设备间难以高效安全联通问题；在工业大数据处理与反馈控制技术方面，研究了面向工业大数据分析的协同机器学习、工业互联网“传—算”耦合机理、面向柔性生产的“产—算—传”三元能力虚拟化方法等技术，解决工业大数据传输与计算割裂、不灵活等问题；在工业互联网平台和应用示范方面，设计开发了工业互联网平台原型系统，并基于此研发了智能云排产和智能云物流等工业互联网应用，进一步验证了“智感、效联、迅知、谐控”关键技术的有效性。总体而言，项目进展顺利，各项技术指标都已达到或超过预期水平。

Application Abstract: This project aims to develop key technologies for cloud-client synergy and build an Industrial Internet platform that integrates human,machines,and objects.During 2017-2019,our project has been focusing on the Industrial Internet architecture,key technologies,platforms,and applications.In terms of the Industrial Internet architecture,we have proposed several mechanisms including a cloud-client synergy framework for Industrial Internet,an edge-based collaborative storage,and cloud-client synergy models.Also,we have designed an Industrial Internet architecture with cloud-client synergy and Intelligence sharing;in terms of sensorless sensing and adaptive sensing of multimedia information,we have proposed an entity identification technology based on commercial Wi-Fi and a video adaptive monitoring technology based on wireless multi-hop networks,which address the sensing-related problems such as limited sensing range,single dimensions,high deployment costs,fixed multimedia information acquisition,and redundant sensing data.In terms of efficient and secure adaptive interconnection,our project focused on the device,data,and service layers,and has proposed efficient interconnection technologies that allow Industrial Internet terminals to achieve secure real-time communication between clients and the cloud.In terms of the Industrial big data processing and feedback control technologies,our project focuses on industrial-oriented collaborative machine learning,the coupling mechanism of the"transmission-calculation"for the Industrial Internet,and the virtualization method based on"production-calculation-transmission"ternary capability for flexible production,to solve the problems in industrial big data transmission and computation.In terms of industrial Internet platforms and applications,we have designed an Industrial Internet platform prototype and developed several Industrial Internet applications such as intelligent industrial scheduling and intelligent cloud logistics,which verify the key technologies of Industrial Internet.Overall,our project is progressing smoothly and all the technical targets have been reached.

项目受资助省

江苏省

项目实施周期(年)

4