A Social Networking Enabled Crowdsourcing System for Integrated Infrastructure Asset Management S. Thomas Ng1; Frank J. Xu2; Yifan Yang3; Hongyang Li4; and Junjie Li5 1
Dept. of Civil Engineering, The Univ. of Hong Kong, Pokfulam, Hong Kong. E-mail:
[email protected] 2 Dept. of Civil Engineering, The Univ. of Hong Kong, Pokfulam, Hong Kong. E-mail:
[email protected] 3 Dept. of Civil Engineering, The Univ. of Hong Kong, Pokfulam, Hong Kong. E-mail:
[email protected] 4 School of Civil Engineering and Transportation, South China Univ. of Technology, Guangzhou 510640, China. E-mail:
[email protected] 5 College of Computer Science and Software Engineering, Shenzhen Univ., Shenzhen 518060, China. E-mail:
[email protected] Abstract Emerging information and communication technologies like building information modeling, internet of things, social networking, cloud computing, big data analytics, mobile application and so on serve as important catalysts to transform the practices of infrastructure asset management (IAM). Owners, occupiers, managers, operators and contractors of infrastructure facilities can now capture, process, share, integrate, and analyze data related to various infrastructure facilities collaboratively and cooperatively to achieve an integrated whole life cycle IAM. This should help improve the overall efficiency of a community and/or city through optimized resource allocation; reduced maintenance and refurbishment cost; less energy consumption; lower risks of service disruption; increased transparency; and better strategic, tactical and operational decisions. This paper outlines the development of a social networking enabled crowdsourcing system for integrated IAM. The system is designed to satisfy the requirements of different stakeholders in managing, operating and repairing a series of interdependent infrastructure facilities. Preliminary studies on the residential sector of Hong Kong reveal that the system could help improve the communication between stakeholders, enhance the transparency and effectiveness of asset management, and reduce the risks of bidrigging in the repair and maintenance schemes. By integrating the proposed system with the existing systems being adopted throughout the entire building life cycle, such as the building information modeling and asset management systems, facility condition, and usage data that is difficult to obtain through traditional means can now be crowdsourced, co-created, or co-processed for facility performance analysis, complaint analysis, and service scheduling analysis. Keywords: Integrated facility management; Social networking; Crowdsourcing; Building maintenance; Renovation and refurbishment. INTRODUCTION Todays infrastructure systems are facing unprecedented challenges ranging from ageing assets, lack of maintenance budget and surging facility usage to the outcry of the society for better service quality. On the other hand, regulations and
guidelines governing climate change mitigation and natural disasters and man-made incidents prevention have posed new requirements on infrastructure systems. To improve the capacity, reliability and sustainability of infrastructure systems, different IAM tools have been introduced to facilitate better planning, operation and maintenance of infrastructure facilities. Despite that, the existing IAM systems are very fragmented with isolated functionalities to satisfy the features and requirements of individual infrastructure systems. In the absence of a unified data exchange regime and an interoperable mega IAM platform, information silos may exist which would subsequently affect the effectiveness of communication and coordination across different infrastructure system owners or operators when joint decisions pertinent to sustainable and resilient infrastructure are made. Thanks to the emerging information and communication technologies (ICT), information can be easily captured, stored and analyzed through sensors, cloud computing, machine learning, and artificial intelligence. By extracting and synthesizing the information collected from different infrastructure systems and owners, an integrated IAM platform can be derived to support decision making. Information and joint analytics capabilities offered by end-users using cutting-edge ICT technologies may add unprecedented value to the decision-making process compared with that underpinned by in-house management systems alone as customer requirements and expectations, user behavior and sentiment, real time operation status of infrastructure systems, and predictions of incident patterns etc. can be mined out from the crowdsourced information. This paper outlines how the IAM practice can be facilitated by the crowdsourcing technologies and practices. A specific case pertinent to building refurbishment is provided to demonstrate how to support decision-making by making reference to the facility condition and usage information crowdsourced from the inhabitants. PREVIOUS WORK Integrated IAM Considerable research and industry efforts have been attributed to the sectorspecific and integrated IAM, scholars put forward abundant frameworks to manage infrastructure assets endorsed by the current best practices and various investigations from a life cycle perspective include the linkage mechanism to integrate various design, construction, operation and maintenance activities (Yuan et al, 2017). While an easy-to-use information management system is always desirable, the interoperability among diverse systems is also a major concern of the integrated IAM practice. To address the issue of interdependency, pilot information frameworks, models and tools including but not limited to a multi-tier component-based framework for integrated municipal IAM (Woldesenbet et al., 2015), a semantic tool to integrate the building information modeling (BIM) and geotechnical information system (GIS) (Karan et al., 2015), a data warehousing to explore the interdependency among multiple infrastructure networks (Shih et al., 2009), etc. have been proposed. These frameworks, models and tools form a solid foundation for further development of an integrated IAM platform.
Potential ICT technologies & emerging crowdsourcing initiatives in Integrated IAM The hot ICT hype topics, such as BIM, internet-of-things (IoT), distributed database, artificial intelligence, machine learning, cloud computing, social networking, etc., have aroused the interests of the AEC sector in recent years. Although ICT and big data technologies present promising potential to capture, store, process and analyze a gigantic volume of heterogeneous data, only few successful applications are reported by the AEC industry (Alavi & Gandomi, 2017). The pioneering works include a collaborative mobile-cloud computing framework for intelligent condition inspection and image-based damage analysis (Chen et al., 2013), and a simulation system for infrastructure systems (Goodall et al., 2013). Crowdsourcing studies have prevailed in marketing operationalization, supply chain management, and information system development. More recently, scholars of the engineering discipline have begun to explore the potential of crowdsourcing for cross-sector IAM, especially for infrastructure maintenance and rehabilitation (Consoli et al., 2015), building energy efficiency management (De Paola et al., 2014), disaster and emergency management (Poblet et al., 2014), and smart transportation management (Misra et al., 2014). The range of crowdsourcing platforms and initiatives include a VGI OpenStreetMap, PetaJakarta.org research project for flooding management (Holderness, 2014), the resilience network initiative supported by Ushahidi Solutions (http://cityresilience.net/what-is-rni.html), etc. A SOCIAL NETWORKING ENABLED CROWDSOURCING SYSTEM FOR INTEGRATED IAM (SCS-IIAM) End users of the system and typical use cases In this paper, a social networking enabled crowdsourcing system for integrated IAM (SCS-IIAM) is proposed. The system can be used by different community stakeholders involved in integrated IAM, such as planners, designers, developers and owners of infrastructure assets; government authorities; public and private investors; consultancy companies; infrastructure operators and maintenance contractors; utility service providers; community managers; facility managers; and users of infrastructure services. Not only would the SCS-IIAM system provide stakeholders with innovative ways to capture, integrate, share and utilize static and dynamic infrastructure asset data for joint planning and collective decision-making, but it could also help enable them to co-create and enhance the resilience, smartness and sustainability of infrastructure facilities in the community. Three representative use cases have been identified when developing SCS-IIAM, and the details are described as follows: (1) Co-constructing and updating as-built building information models (BIMs) for integrated IAM. As illustrated in Figure 1, this use case defines the interactions between different actors and the SCS-IIAM for reconstructing or updating the BIM data of built infrastructure assets (Bradley et al, 2016). The actors could be the users of infrastructure facilities; infrastructure service providers; modeling systems that automatically generate the infrastructure BIMs from laser-scanned point clouds; types of off-the-shelf or proprietary information systems that aid integrated IAM, e.g. CAFM, GIS, CMMS and FM systems; integrated IAM
engineers; integrated IAM managers; and administrators who orchestrate and supervise the generation and updating of infrastructure BIMs. The sequence of this use case shall include: the importing of as-built geometric infrastructure models into the SCS-IIAM, crowdsourcing and enriching the details of different infrastructure components, verifying the consistence and completeness of the BIMs, and applying changes to and publishing new versions of infrastructure BIMs. SCS-IIAM System Infrastructure Service Users
Actors (Persons and Organizations)
Actors (Systems)
IIAM Engineers
Co-construct / update BIMs IIAM Managers
Infrastructure BIM Administrators
Figure 1. Co-constructing / updating infrastructure BIMs (2) Crowdsourcing and retrieving infrastructure operation and condition data like service status, breakdowns, defects, damages and deteriorations. This use case describes how end-users can employ the SCS-IIAM to report and share real-time data related to infrastructure operation and condition. Community infrastructures can be considered as a socio-eco-technical system (Grabowski et al. 2017). Being an intelligent agent, the SCS-IIAM can assist different users to capture, sense, contribute, integrate, share and retrieve infrastructure data on demand. For example, citizens can report any service failures or deteriorations of the buildings and transportation networks; maintenance contractors can enquire the location, maintenance history and operation status of urban water supply and wastewater treatment systems in vicinity to the buildings; and transportation departments can inform citizens of the service disruptions and provide update on the progress of repair and maintenance. In this use case, the infrastructure BIMs will act as a thread to orchestrate and associate all the crowdsourcing data processes. (3) Co-creating infrastructure sustainability and resilience. This use case demonstrates the steps of how end-users can leverage the SCS-IIAM to co-create community sustainability and resilience. Building resilience and achieving integrated sustainability demands flexible and deep collaboration among various stakeholder groups. The SCS-IIAM can help gather comprehensive understanding of natural disasters and man-made hazards that threaten the entire community; investigate the interdependency and interactions among different infrastructure components; set aligned sustainability and resilience goals according to distinctive perspectives; synergize resilience management processes; streamline data aggregation and integration efforts for resilience monitoring and evaluation;
unify resilience and sustainability metrics; and ultimately identify the gaps for consistent actions and continuous resilience improvement. General architecture of the SCS-IIAM prototype system As illustrated in Figure 2, the SCS-IIAM is designed with a multi-layered architecture that consists of over twelve modules including: an infrastructure big data repository, infrastructure BIMs repository, infrastructure master data management engine and repository, enterprise data integration engine, social networking data integration engine, online community management engine, crowdsourcing process management engine, integrated IAM process management and data service engine, integrated IAM resilience management engine, integrated IAM analytics service engine, building information modeling engine, and a set of front-end mobile or webbased applications. Due to the length limitation of this paper, only six important modules are described as below:
Figure 2. Schematic diagram of the general architecture of SCS-IIAM (1) Infrastructure big data repository. This component is a logical / distributed data repository / lake for storing a high-volume and high-variety of static infrastructure data (e.g. the location and GIS spatial data, and historical operation and maintenance records); crowdsourced real-time infrastructure condition data; images and videos of infrastructure disruptions; and the citizens feedback and behavioral data regarding the use of community infrastructures. The repository / lake is designed to combine the strengths of traditional database and data warehousing with big data technologies (e.g. Hadoop, Spark, Storm and HBASE) as well as with flexible data management and access strategies. (2) Infrastructure BIMs repository. This repository stores the building information models of built community infrastructures in various levels of details. Regarding the long life span of infrastructures as well as the diverse requirements of
different stakeholders across different integrated IAM processes (e.g. planning, design, construction, maintenance, facility and utility management, refurbishment and renovation and deconstruction, performance evaluation, and end-of-life considerations), an incremental update approach should be used to maintain the trackable versions of BIMs. Besides, this module also extends the open standards of BIM and 3D GIS, namely IFC4 schema and CityGML respectively, to map infrastructures BIM semantic building information with their GIS spatial data, so as to integrate the smart infrastructure data sensing with the IoT systems, and to facilitate the crowdsourcing infrastructure condition data. (3) Infrastructure master data / metadata management engine. This engine aims to address the data quality and data integration challenges and obstacles that impact the efficiency and effectiveness of integrated IAM or hinder its large-scale adoption across multiple organizations and sectors which could impede the coordination among the stakeholders, in term of data inconsistence, inaccuracy, incompleteness, delay and irrelevance. The master data defines the consistent and uniform set of temporal and spatial identifiers and the extended attributes of infrastructures that describes the principal entities of infrastructure socio-ecotechnical systems, such as the infrastructure sectors, infrastructure category hierarchies, operating instructions, service suppliers and customers, sites, hazard types, and performance and resilience indicators etc. This engine also provides some data cleansing and data transformation functions to support infrastructure data analytics applications for integrated decision-making. (4) Online community management engine. This module is responsible for the endusers roles and privacy management. Community citizens, utilities operators, maintenance contactors, government agencies and other relevant stakeholders can access the SCS-IIAM with their social networking accounts they have created in different social networking platforms. By leveraging the industry-standard protocol and framework for authorization and privacy control (e.g. OAuth 2.0), the component is supposed to provide integration capabilities with no-less-than four popular social networking platforms, e.g. Facebook, Twitter, WhatApps, WeChat and Sina Weibo. It could enable the users of the SCS-IIAM to capture and disseminate infrastructure information rapidly through their followers and friends on these platforms. The users can also manage their different accounts hosted on one or more social networking platforms using this component, e.g. updating profile information, setting privileges and rules for accessing sensitive and privacy information, and maintaining followers and friends. (5) Crowdsourcing process management engine. This component manages the bottom-up and top-down processes for crowdsourcing infrastructure BIMs and condition data. The processes may include task division, participant selection, priorities setting, feedback solicitation, data aggregation and verification, activity monitoring, polling on ideas or decisions, rewards management, etc. The engine is developed by extending the open-source business process management engine, BIM and visualization engine. This component can be plugged into traditional sector-specific IAM systems to assist relevant stakeholders initiating the crowdsourcing tasks or pulling / subscribing crowdsourced infrastructure BIMs and condition data for agile integrated IAM.
(6) Integrated IAM resilience management engine. This subsystem supports the operation management of infrastructure and community resilience. It can help stakeholders plan for, absorb, respond to, recover from, and successfully adapt to natural and man-made adverse events; and enable them to crowdsource, assemble, integrate, assimilate and analyze fragmented data maintained by owners or operators of various community infrastructure systems. The engine can be deployed to better understand the impacts of citizens behaviors related to the use of infrastructure systems on infrastructure resilience; to explore the interdependency among different community components; to alert citizens the anticipated natural hazards and infrastructure service disruptions; to sense and infer citizens concerns against adverse events; and to solicit and share ideas for improving community resilience. Design and Implementation features The SCS-IIAM system is envisioned to expose crowdsourcing and crowdsensing functions as fine-tuned services, and provide end-users with novel applications for them to actively participate in the integrated management of smart community infrastructures, as well as to improve infrastructure resilience and community sustainability. The system can be deployed into or integrated with types of cloud computing environments such as a public, private and hybrid cloud. The prototype is designed by referring to the state-of-the-art software architecture technologies, such as microservice and event-driven software patterns, model-driven approach, complex event processing engine, and cloud computing architecture (e.g. infrastructure as a service, platform as a service, software as a service, integration as a service, analytics as a service, and master data management as a service). The SCS-IIAM prototype is developed by making reference to the published IAM guidelines (e.g. the International Infrastructure Management Manual and ISO 55000), BIM standards (e.g. ISO 29481 and NBIMS-US), smart city standards (e.g. ISO 37120, 37121), and emerging smart information models and sustainability and resilience metrics. The prototype is implemented using the latest and proven open source social networking and big data analytics technologies, and other relevant information technologies. They include but are not limited to the SQL databases and NoSQL databases (e.g. Hadoop and MongoDB); machine-to-machine communication gateway; machine learning library (e.g. MLib); popular programming languages that work well with big data (e.g. Python, Pig, Hive) technology stack; IoT middleware; real-time complex event processing engine; open source geographic information and global position systems; big data integration and analytics software; interactive data visualization packages; BIM engine and toolkit (e.g. BIM server); as well as data mining and social network mining technologies developed by the authors. CASE STUDY- FACILITES MAINTENANCE & REFURBISHMENT Requirement analysis Ageing buildings beset communities in Hong Kong. Building inspection and maintenance is imperative to achieve sustainable community, and a long-term holistic measure named Mandatory Building Inspection Scheme (MBIS) is proposed by the Government of Hong Kong to resolve the building deterioration problem. However,
some major difficulties are still encountered during the MBIS implementation. The most two profound investigated by Chan and Choi (2015) include: (i) difficulty in coordinating the individual flat owners, owners corporation and property management company; and (ii) ignorance of building repair, weak building-care culture, and wait-and-see attitude of individual owners. Moreover, individual owners also express their concerns about insufficient skills for building maintenance, affordability of maintenance and rehabilitation cost, and potential corruption when selecting the Registered Inspector (RI) and Registered Contractor (RC). A social network enabled crowdsourcing platform for asset management could enhance the MBIS implementation by meeting the stakeholders urgent requirements of: (i) sufficient visual as-built information to facilitate the fault reporting by individual owners; (ii) user-friendly interface to allow individual owners uploading their comments, photos and videos; (iii) systematic and transparent eventhandling procedure and information disclosure; and (iv) timely decision making by property management company to rectify the defects and problems. Pilot deployment of the prototype system and preliminary results To test and demonstrate the applicability of the SCS-IIAM prototype, some components of the system including the building condition data and BIMs crowdsourcing engine, online community management engine and crowdsourcing process management engine, etc. are being piloted to orchestrate the facility management and mandatory maintenance of an old building located in Hong Kong. The 26-years-old private residential building used for the case study has over 100 flats occupied by 300 owners or tenants. In 2012, the building owners received several government mandatory orders demanding them to carry out repair and maintenance works to the defective building fabrics (e.g. external wall, reinforced concrete structure, and roofs and windows), fire doors, water tanks and lifts, defective rainwater and sewage pipes, and building HVAC system. Owners could be prosecuted and fined for an offence of the Building Ordinance if they fail to comply with the requirements of these orders. However, fulfilling these orders and conducting maintenance works properly is a very complicated and costly task as it would not only require comprehensive and tailor-made professional knowledge, but it could also necessitate the collective decision of all owners and the close cooperation of all stakeholders. Apart from that, owners are exposed to the risks of bid-rigging and price inflation when undertaking the building maintenance projects. Before the pilot, the building owners have already established voluntary online groups using different social networking platforms to exchange fragmented opinions pertinent to the maintenance works, but in a non-coordinated and less efficient way. The preliminary results of the pilot study show that the SCS-IIAM could enable building owners and the owners corporation to establish effective communication channels with property management companies and other stakeholders for undertaking the maintenance projects; support the owners corporation members in initiating, organizing, supervising and appraising repair and maintenance works; help the building owners solicit professional knowledge and collect reliable reference cost information regarding the building management and maintenance services; assist them selecting consultants and contractors for the repair
solutions; aid the assessment of building conditions and detecting building defects via collective cooperation; better engage stakeholders to co-generate BIMs details for building facility management and maintenance; and finally improve the transparency and effectiveness of residential building management and maintenance. According to our preliminary investigation, over a half of the residents in the pilot building show their interests in using SCS-IIAM to facilitate the fault reporting. In addition, there are more than 40,000 private buildings and over 90 property management companies in Hong Kong. It is expected that the potential system would have a prosperous future in enhancing the facility management practice in Hong Kong. DISCUSSION AND FUTURE WORK The advance of emerging ICT technologies like BIM, IoT, social networking, mobile and cloud computing, big data analytics and artificial intelligence are transforming the traditional practices of IAM. These technologies have a great potential to enhance the engagement, collaboration and cooperation of various infrastructure stakeholders (e.g. community citizens, owners, developers, operators, government departments and service contractors) in order to improve the overall efficiency, sustainability and resilience of the socio-eco-technical systems. For example, with easy-to-use mobile applications stakeholders can co-generate the BIMs details of the infrastructure system, contribute data pertinent to the infrastructure condition and service disruption, share knowledge and lessons for building repair and maintenance, and co-monitor and co-create community sustainability and resilience. This paper presents the development of a social networking enabled crowdsourcing system for IAM (SCS-IIAM). The system is devised to satisfy the requirements of different stakeholders in managing, operating and repairing a series of interdependent infrastructure facilities. Besides the use cases and pilots outlined in this paper, the software architecture and the SCS-IIAM can be applied to the integration management of other type of infrastructure networks (e.g. bridges, transportation assets, water and energy utilities). The key required modification would be sector-specific domain knowledge, data and information models, integration with existing systems, etc. Comparison is being conducted to investigate the benefits and limits of crowdsourcing approach with existing IAM practices and procedures. To verify the practicality of the SCS-IIAM further, certain components of the SCS-IIAM would still need to be accomplished and tested for different integrated IAM use scenarios. Moreover, it is necessary to the fill the research and development gaps of: (i) enhancing the integration capabilities of the SCS-IIAM with third party IAM and facility management systems; (ii) enriching the functions of the SCS-IIAM for infrastructure master data and metadata management; (iii) implementing more tools for interactive modeling, rendering, editing and archiving of BIMs; (iv) adding more analytical functions for analyzing the sustainability and resilience of community infrastructure systems; and (iv) exploring the patterns of deploying the SCS-IIAM on different cloud computing platforms.
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