Purpose

To mitigate the problems in sensor-based facility management (FM) such as lack of detailed visual information about a built facility and the maintenance of large scale sensor deployments, an integrated data source for the facility’s life cycle should be used. Building information modeling (BIM) provides a useful visual model and database that can be used as a repository for all data captured or made during the facility’s life cycle. It can be used for modeling the sensing-based system for data collection, serving as a source of all information for smart objects such as the sensors used for that purpose. Although few studies have been conducted in integrating BIM with sensor-based monitoring system, providing an integrated platform using BIM for improving the communication between FMs and Internet of Things (IoT) companies in cases encountered failed sensors has received the least attention in the technical literature. Therefore, the purpose of this paper is to conceptualize and develop a BIM-based system architecture for fault detection and alert generation for malfunctioning FM sensors in smart IoT environments during the operational phase of a building to ensure minimal disruption to monitoring services.

Design/methodology/approach

This paper describes an attempt to examine the applicability of BIM for an efficient sensor failure management system in smart IoT environments during the operational phase of a building. For this purpose, a seven-story office building with four typical types of FM-related sensors with all associated parameters was modeled in a commercial BIM platform. An integrated workflow was developed in Dynamo, a visual programming tool, to integrate the associated sensors maintenance-related information to a cloud-based tool to provide a fast and efficient communication platform between the building facility manager and IoT companies for intelligent sensor management.

Findings

The information within BIM allows better and more effective decision-making for building facility managers. Integrating building and sensors information within BIM to a cloud-based system can facilitate better communication between the building facility manager and IoT company for an effective IoT system maintenance. Using a developed integrated workflow (including three specifically designed modules) in Dynamo, a visual programming tool, the system was able to automatically extract and send all essential information such as the type of failed sensors as well as their model and location to IoT companies in the event of sensor failure using a cloud database that is effective for the timely maintenance and replacement of sensors. The system developed in this study was implemented, and its capabilities were illustrated through a case study. The use of the developed system can help facility managers in taking timely actions in the event of any sensor failure and/or malfunction to ensure minimal disruption to monitoring services.

Research limitations/implications

However, there are some limitations in this work which are as follows: while the present study demonstrates the feasibility of using BIM in the maintenance planning of monitoring systems in the building, the developed workflow can be expanded by integrating some type of sensors like an occupancy sensor to the developed workflow to automatically record and identify the number of occupants (visitors) to prioritize the maintenance work; and the developed workflow can be integrated with the sensors’ data and some machine learning techniques to automatically identify the sensors’ malfunction and update the BIM model accordingly.

Practical implications

Transferring the related information such as the room location, occupancy status, number of occupants, type and model of the sensor, sensor ID and required action from the BIM model to the cloud would be extremely helpful to the IoT companies to actually visualize workspaces in advance, and to plan for timely and effective decision-making without any physical inspection, and to support maintenance planning decisions, such as prioritizing maintenance works by considering different factors such as the importance of spaces and number of occupancies. The developed framework is also beneficial for preventive maintenance works. The system can be set up according to the maintenance and time-based expiration schedules, automatically sharing alerts with FMs and IoT maintenance contractors in advance about the IoT parts replacement. For effective predictive maintenance planning, machine learning techniques can be integrated into the developed workflow to efficiently predict the future condition of individual IoT components such as data loggers and sensors, etc. as well as MEP components.

Originality/value

Lack of detailed visual information about a built facility can be a reason behind the inefficient management of a facility. Detecting and repairing failed sensors at the earliest possible time is critical to ensure the functional continuity of the monitoring systems. On the other hand, the maintenance of large-scale sensor deployments becomes a significant challenge. Despite its importance, few studies have been conducted in integrating BIM with a sensor-based monitoring system, providing an integrated platform using BIM for improving the communication between facility managers and IoT companies in cases encountered failed sensors. In this paper, a cloud-based BIM platform was developed for the maintenance and timely replacement of sensors which are critical to ensure minimal disruption to monitoring services in sensor-based FM.

中文翻译：

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将 BIM 集成到基于传感器的设施管理操作中

目的

为了缓解基于传感器的设施管理 (FM) 中的问题，例如缺乏关于已建成设施的详细视觉信息和大规模传感器部署的维护，应使用设施生命周期的集成数据源。建筑信息模型 (BIM) 提供了有用的可视化模型和数据库，可用作设施生命周期中捕获或制作的所有数据的存储库。它可用于对基于传感的数据收集系统进行建模，作为智能对象（例如用于该目的的传感器）的所有信息源。虽然很少有研究将 BIM 与基于传感器的监控系统集成，在遇到传感器故障的情况下，使用 BIM 提供集成平台以改善 FM 和物联网 (IoT) 公司之间的通信在技术文献中受到的关注最少。因此，本文的目的是概念化和开发基于 BIM 的系统架构，用于在建筑物的运营阶段对智能物联网环境中的故障​​ FM 传感器进行故障检测和警报生成，以确保对监控服务的干扰最小化。

设计/方法/方法

本文描述了在建筑物运营阶段检查 BIM 在智能物联网环境中有效传感器故障管理系统的适用性的尝试。为此，在商业 BIM 平台中对具有四种典型类型的 FM 相关传感器以及所有相关参数的七层办公楼进行建模。在可视化编程工具 Dynamo 中开发了一个集成的工作流程，将相关的传感器维护相关信息集成到一个基于云的工具中，从而在建筑设施经理和物联网公司之间为智能传感器管理提供一个快速高效的通信平台。

发现

BIM 中的信息可以让建筑设施管理人员做出更好、更有效的决策。将 BIM 中的建筑和传感器信息集成到基于云的系统中，可以促进建筑设施经理和物联网公司之间更好的沟通，从而实现有效的物联网系统维护。使用可视化编程工具 Dynamo 中开发的集成工作流程（包括三个专门设计的模块），该系统能够自动提取所有基本信息，例如故障传感器的类型及其模型和位置，并将其发送给物联网公司。传感器故障事件使用云数据库，对传感器的及时维护和更换有效。实施了本研究中开发的系统，并通过案例研究说明了其功能。

研究限制/影响

然而，这项工作存在一些局限性，如下所示：虽然本研究证明了在建筑物监控系统的维护规划中使用 BIM 的可行性，但可以通过集成某些类型的传感器（如占用率）来扩展开发的工作流程传感器到开发的工作流程，以自动记录和识别居住者（访客）的数量，以优先维护工作；开发的工作流程可以与传感器的数据和一些机器学习技术集成，以自动识别传感器的故障并相应地更新 BIM 模型。

实际影响

将房间位置、占用状态、占用人数、传感器类型和型号、传感器 ID 和所需操作等相关信息从 BIM 模型传输到云端，这将非常有助于物联网公司提前实际可视化工作空间，并计划在没有任何物理检查的情况下及时有效地做出决策，并支持维护计划决策，例如通过考虑空间的重要性和占用数量等不同因素来确定维护工作的优先级。开发的框架也有利于预防性维护工作。该系统可以根据维护和基于时间的到期时间表进行设置，自动与 FM 和 IoT 维护承包商共享有关 IoT 部件更换的警报。

原创性/价值

缺乏有关已建成设施的详细视觉信息可能是设施管理效率低下的一个原因。尽早检测和修复故障传感器对于确保监控系统的功能连续性至关重要。另一方面，大规模传感器部署的维护成为一项重大挑战。尽管 BIM 很重要，但很少有研究将 BIM 与基于传感器的监控系统集成，提供一个使用 BIM 的集成平台，以在遇到传感器故障的情况下改善设施管理人员和物联网公司之间的通信。在本文中，开发了一个基于云的 BIM 平台，用于维护和及时更换传感器，这对于确保基于传感器的 FM 中的监控服务的中断最小化至关重要。