Leveraging BIM and Big Data to deliver well maintained highways

Abstract

Purpose -Effective management of highways requires management of diverse data sets including traffic volume data, roadway, and road edge and road-side data. Like all major infrastructure clients, highways administration authorities are under pressure to use such platforms for better management of data that, in addition to creating other opportunities, allows improved life cycle management of asset data and predictive analytics. This paper aims to review such opportunities and the value that can be generated through integrated life cycle data management by leveraging Big Data and building information modelling (BIM).Design/methodology/approach -A literature review is initially performed to systematically gather information to identify and understand BIM as a collaborative platform. Data management applications in other industries are also reviewed. Interviews were conducted and two industry workshops were organised to understand BIM implementation challenges within highways development projects and the role BIM can play in bridging inefficiencies resulting from loss of information at handover phases. The overall understanding lead to drawing up user needs, gathering system requirements and eventually a system architecture design to promote efficient information management throughout the asset lifecycle.Findings -It is observed that data from the design and construction phases of projects can be used to inform asset registers from an earlier stage. This information can be used to plan maintenance schedules. Moreover, it can also be integrated with data generated from numerous other sensors to develop a better picture of network operations and support key decision-making. Effective road network management involves collection and analysis of huge data from a variety of sources including sensors, mobiles, assets and Open Data. Recent growth in Big Data analytics and data integration technologies provides new opportunities to optimise operations of highways infrastructure.Research limitations/implications -The system architecture designed for this research is translated into a prototype system as a proof of concept. However, it needs to be tested and validated by end users to be transformed into a useful solution for the industry.Originality/value -This paper provides an enhanced understanding of new opportunities created to optimise operations of highways infrastructure using the recent growth in Big Data analytics and data integration technologies.

Building Information Modeling (BIM) for Structural Engineering: A Bibliometric Analysis of the Literature

“…Structural engineering is a subset of civil engineering [46]. Available studies have targeted different issues of civil engineering projects concerning BIM: developments of BIM implementations [13]; communication modes [47]; information management frameworks [10]; refurbishment of historic buildings using BIM [16,48]; implementation of BIM to existing buildings [49]; sustainable buildings [8,50]; BIM adoption in different civil infrastructure facilities [26]; roles and responsibilities of BIM practitioners [51]; conceptualization of a BIM-based facilities management framework [52,53]; visualization technologies in safety management [21,23]; data classifications [54]; BIM knowledge mappings [14]; BIM research categories [55]; application of laser scan technology [56]; challenges facing the facilities management sector [52,57,58]; application of semantic web technologies; issues and recommendations for BIM and life cycle assessment tools [59]; BIM and GIS [60]; green BIM [61]; collaboration in BIM networks [19]; transportation infrastructure; road infrastructure [62]; highway maintenance [17]; role of BIM in generating big data [37], etc. ese studies have added much value to the BIM literature and have explored a wide range of fields associated with civil engineering.…”

“…ere have been some in-depth reviews on BIM in general [9,[13][14][15] and studies that have dealt with specific fields like transportation infrastructure, heritage buildings [16], civil infrastructure maintenance [17], collaborative management [18][19][20], health and safety [21][22][23], contractors [10], and academics aspects [24,25]. Research on the integration of BIM within civil engineering is still in its infancy [9].…”

Bim and Gis Integration for Infrastructure Asset Management: A Bibliometric Analysis

“…Integration and decision making: Considering transportation infrastructure, Aziz et al (2017) proposed the use of an open-source cloud computing platform, Hadoop, to allow for continuous flow of data throughout an asset's life cycle; while, Sankaran et al (2018) considered the potential benefit of using Civil Integrated Management (CIM), a set of practices and tools that can facilitate the workflow of highway project delivery and management. Other authors presented frameworks for utility infrastructure management: Edmondson et al (2018) developed a prototype to aid prediction and decision making about a sewerage network; Lee et al (2018) presented a framework, based on the integration of BIM/GIS, to improve performance of current maintenance management system; Love et al (2018) developed a System Information Model (SIM), in which each component has geometric data (3D model), non-geometric data (type and functionality) and geographic data.…”

An assessment on the parallel impacts of building information modeling and big data on project operation and maintenance

“…Integration of big data and BIM was proposed on effective and optimized management of highway which is required variety of data from traffic and roadway data, in order to do so, creating a platform for data management is essential which can also provide more value based on collected data in lifecycle data management [27].…”