Integrating Internet of Things (IoT), Advanced Analytics and Immersive Computing to Enable Cognitive BIM

最近，人们对通过将建筑信息建模(BIM)与新兴的数字技术(如物联网(IoT)和虚拟/增强现实(VR/AR))相结合来改进设施生命周期管理(FLCM)活动的兴趣激增。虽然这些新的协同效应显示出巨大的潜力，但重大的研究空白仍然限制了这些技术的共同好处。 主要挑战之一是这些技术学科的数据生态系统之间缺乏足够的语义互操作性。这一缺陷主要源于与封闭的数据生态系统的紧密联系，这阻碍了在设施的整个生命周期中进行有效的跨域数据交换。最近使用形式本体和语义网技术来解决构建环境的互操作性的研究已经显示出令人振奋的结果。然而，对于BIM-IoT集成，这些方法的应用还有待更广泛的研究。 仅仅统一FLCM数据不会增加太多价值。收集的各种数据应该首先进行融合，然后转化为有用的信息/知识。此外，需要各种推论来检索相关信息/知识，将其作为辅助目标从业者的决策支持系统(DSS)的输入。然而，由于人类干预仍将是一个关键因素，将数据分析与严肃的游戏相结合，有望通过增强此类环境提供的可视化和交互来提供更多机会。 为了提供丰富的BIM、IoT和严肃游戏环境的协调，该提案调查了“认知BIM”：一个框架，用于创建能够感知、学习和交互的设施的以BIM为中心的自我进化的数字孪生兄弟。为了实现这一长期愿景，在7名学生的参与下，制定了四个短期目标：两名博士、四名硕士和一名本科生。首先，将研究本体和语义网技术的应用，以集成BIM、IoT和记录的生命周期数据。接下来，将提出一个数据分析框架，以应用各种先进的数据挖掘方法。然后，将开发一个基于本体的框架，以检索上下文相关的信息/知识并提供特定于领域的决策支持系统。最后，该框架将扩展到开发支持VR/AR的界面，并将及时洞察的丰富可视化传达给各种利益相关者(例如，设计师、施工者、设施经理)，从而帮助他们基于启发式解决问题并纳入他们的直观反馈。 拟议的研究成果将有助于建筑环境的可持续发展，为智能城市的实现铺平道路，在智能城市中，不同设施(如建筑、桥梁和隧道)的单个数字孪生兄弟可以实时分享见解，并智能和集体行动。

Recently, there has been a surge of interest in the improvement of Facility Life-Cycle Management (FLCM) activities by integrating Building information modeling (BIM) with emerging digital technologies, such as Internet of Things (IoT) and Virtual/Augmented Reality (VR/AR). While these new synergies show great potential, major research gaps still limit the joint benefits of such technologies. One of the primary challenges is the lack of sufficient semantic interoperability between the data ecosystems of these technological disciplines. This shortcoming mainly stems from strong ties to closed data ecosystems, which impede effective cross-domain data exchange throughout the lifecycle of facilities. Recent research using formal ontologies and semantic web technologies to address interoperability for the built environment has shown promising results. However, the application of such approaches has yet to be more extensively investigated for BIM-IoT integration. Mere unification of FLCM data does not add much value. The diverse collected data should first be fused and then transformed into useful information/knowledge. Additionally, various inferences are required to retrieve relevant information/knowledge as input to Decision Support Systems (DSS) designed to assist target practitioners. Yet, since human intervention will remain as a key element, integrating data analytics with serious games promises further opportunities by enhancing the visualizations and interactions provided by such environments. To deliver rich orchestrations of BIM, IoT, and serious game environments, this proposal investigates “Cognitive BIM”: a framework for creating BIM-centred and self-evolving digital twins of facilities capable of sensing, learning, and interacting. To meet this long-term vision, four short-term objectives have been established with the involvement of 7 students: two Ph.D., four M.Sc., and one undergraduate student. First, the application of ontologies and semantic web technologies will be investigated to integrate BIM, IoT, and recorded lifecycle data. Next, a data analytics framework will be presented to apply various advanced data-mining methods. Then, an ontology-based framework will be developed to retrieve contextually relevant information/knowledge and feed domain-specific DSS. Finally, the framework will be expanded to develop VR/AR-enabled interfaces and convey rich visualizations of timely insights to various stakeholders (e.g., designers, constructors, facility managers), thereby assisting them in heuristics-based problem-solving and incorporating their intuitive feedback. Results of the proposed research will contribute to the sustainable development of the built environment by paving the road for the actualization of smart cities in which individual digital twins of different facilities, such as buildings, bridges, and tunnels, can share insights in real-time and act intelligently and collectively.