Big data for smart operations and maintenance of buildings

Motawa, Ibrahim (2017) Big data for smart operations and maintenance of buildings. In: 15th International Operation and Maintenance Conference, 2017-10-23 - 2017-10-25.

[img]
Preview
Text (Motawa-IOMC-2017-Big-data-for-smart-operations-and-maintenance-of-buildings)
Motawa_IOMC_2017_Big_data_for_smart_operations_and_maintenance_of_buildings.pdf
Accepted Author Manuscript

Download (646kB)| Preview

    Abstract

    The trend in industry to move towards smart buildings will in turn necessitate the move to smart operations and maintenance. As buildings lifecycle continues for a number of decades, various data about performance and operations need to be captured. There are various smart data collection tools available such as: mobile devices, social media, smart meters, sensors, satellites, camera footage, traffic flow reports, etc.. The analysis of the collected data can provide huge feedback for better buildings management. This research aims to adopt the concept of Big Data to capture the information and the knowledge of buildings operations; particularly for building maintenance and refurbishment. With the use of Building Information Modelling (BIM) systems to store various structured data of buildings, the unstructured data for various buildings operations will be also captured. For this purpose, a new system is proposed that integrates cloud-based Spoken Dialogue System (SDS), case-based reasoning, and BIM system. The proposed smart system acts as an interactive expert agent that seeks answers from buildings managers/users about building maintenance problems and help searching for solutions from previously stored knowledge cases. Capturing multi-modes data into BIM systems using the cloud-based spoken dialogue systems can utilise the high volume of data generated over building lifecycle. This can help design and operation teams to manage buildings, spaces, and services more efficiently. The data capture tools (including SDS) provide granular real-time data about utilization patterns which can improve the maintenance of buildings services and operations.