IoT-Enabled Data-Driven Collaborative Intelligent Systems

支持物联网的数据驱动的协作智能系统

• 批准号: RGPIN-2018-05651
• 负责人: Shen, Weiming
• 金额: $ 2.29万
• 依托单位: University of Western Ontario
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=665001
• 关键词: IoT; Enabled; Data; Driven; Collaborative

Internet of Things (IoT) has been widely accepted as a novel paradigm that can radically transform industry and society. It can realize the seamless integration of various devices equipped with sensing, identification, processing, communication, actuation, and networking capabilities. On the other hand, Big Data is a broad term for data sets so large or complex that traditional data processing technologies are inadequate. It has recently been considered as a technology and become a very active research area primarily involving topics related to machine learning, database, and distributed computing. It has been claimed that “the success or failure of the Internet of Things hinges on Big Data”.******IoT and Big Data bring great opportunities to improve agent-based collaborative intelligent systems that have been proposed, developed, and deployed during the past twenty-five years. However, these new technologies also bring significant challenges and do not address major issues such as system reliability, security, efficiency, and trust management. Significant R&D efforts are required before these technologies can be widely deployed in industrial applications.******The long-term goal of this research program is to develop scientific and engineering foundations, innovative technologies and solutions for IoT-enabled data-driven collaborative intelligent systems, with particular attention to the application domain of intelligent buildings.******At the fundamental research level, the focus will be on the development an IoT-enabled data-driven platform for integrating Cloud Computing, IoT, Big Data, agent, and blockchain technologies for collaborative intelligent systems. The resulting platform and related technologies will be generic enough for applications to different industrial domains, including intelligent buildings, smart homes, smart factories, and smart cities.******In the intelligent building application domain, the focus will be on the development of Big Data analytic techniques and solutions for automated fault detection, diagnostics and failure prediction. Finally, all the resulting technologies and solutions will be validated and demonstrated through pilot implementations.******This research will result in substantial advancements in understanding, modelling, designing, and implementing IoT-enabled data-driven collaborative intelligent systems. The resulting technologies will have a world-wide clientele and will put Canadian industries and universities in forefront of innovation, and help Canada emerge as a global technology leader. The proposed research program will also offer a great HQP training opportunity and provide Canadian industries with potential experts in collaborative intelligent systems and intelligent buildings, a profession believed to be in high demand in the next five to ten years.

物联网（IoT）已被广泛接受为一种新的范式，可以从根本上改变工业和社会。它可以实现配备传感，识别，处理，通信，致动和联网能力的各种设备的无缝集成。另一方面，大数据是一个广义的术语，指的是如此庞大或复杂的数据集，以至于传统的数据处理技术是不够的。它最近被认为是一种技术，并成为一个非常活跃的研究领域，主要涉及与机器学习，数据库和分布式计算相关的主题。有人说，“物联网的成败取决于大数据”。物联网和大数据为改进在过去25年中提出、开发和部署的基于代理的协作智能系统带来了巨大的机会。然而，这些新技术也带来了重大挑战，并没有解决系统可靠性、安全性、效率和信任管理等重大问题。在这些技术广泛应用于工业应用之前，需要进行大量的研发工作。*该研究计划的长期目标是为物联网数据驱动的协作智能系统开发科学和工程基础，创新技术和解决方案，特别关注智能建筑的应用领域。在基础研究层面，重点将是开发一个支持物联网的数据驱动平台，用于集成云计算，物联网，大数据，代理和区块链技术，以实现协作智能系统。由此产生的平台和相关技术将足够通用，适用于不同的工业领域，包括智能建筑，智能家居，智能工厂和智能城市。在智能建筑应用领域，重点将是开发大数据分析技术和自动故障检测、诊断和故障预测解决方案。最后，所有由此产生的技术和解决方案将通过试点实施进行验证和演示。******这项研究将在理解、建模、设计和实施物联网数据驱动的协作智能系统方面取得实质性进展。由此产生的技术将拥有全球客户，并将使加拿大的工业和大学处于创新的前沿，并帮助加拿大成为全球技术领导者。拟议的研究计划还将提供一个很好的HQP培训机会，并为加拿大工业提供协作智能系统和智能建筑方面的潜在专家，这一专业在未来五到十年内将有很高的需求。