Supporting smart construction with dependable edge computing infrastructures and applications

Abstract The Internet of Things (IoT) such as the use of robots, sensors, actuators, electronic signalization and a variety of other Internet enabled physical devices may provide for new advanced smart applications to be used in construction in the very near future. Such applications require real-time responses and are therefore time-critical. Therefore, in order to support collaboration, control, monitoring, supply management, safety and other construction processes, they have to meet dependability requirements, including requirements for high Quality of Service (QoS). Dependability and high QoS can be achieved by using adequate number and quality of computing resources, such as processing, memory and networking elements, geographically close to the smart environments. The goal of this study is to develop a practical edge computing architecture and design, which can be used to support smart construction environments with high QoS. This study gives particular attention to the solution design, which relies on latest cloud and software engineering approaches and technologies, and provides elasticity, interoperability and adaptation to companies' specific needs. Two edge computing applications supporting video communications and construction process documentation are developed and demonstrate a viable edge computing design for smart construction.

[1]  Yong Zhao,et al.  Cloud Computing and Grid Computing 360-Degree Compared , 2008, GCE 2008.

[2]  Vlado Stankovski,et al.  Implementing time-critical functionalities with a distributed adaptive container architecture , 2016, iiWAS.

[3]  Shankar Chakraborty,et al.  A software prototype for material handling equipment selection for construction sites , 2015 .

[4]  Radu Prodan,et al.  Use Cases towards a Decentralized Repository for Transparent and Efficient Virtual Machine Operations , 2017, 2017 25th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP).

[5]  Carl E. Landwehr,et al.  Basic concepts and taxonomy of dependable and secure computing , 2004, IEEE Transactions on Dependable and Secure Computing.

[6]  Christian Bonnet,et al.  DataTweet: An architecture enabling data-centric IoT services , 2016, 2016 IEEE Region 10 Symposium (TENSYMP).

[7]  Rajiv Ranjan,et al.  Osmotic Computing: A New Paradigm for Edge/Cloud Integration , 2016, IEEE Cloud Computing.

[8]  Luis Rodero-Merino,et al.  Finding your Way in the Fog: Towards a Comprehensive Definition of Fog Computing , 2014, CCRV.

[9]  Weisong Shi,et al.  Edge Computing: Vision and Challenges , 2016, IEEE Internet of Things Journal.

[10]  Ian Taylor,et al.  Runtime Network-level Monitoring Framework in the Adaptation of Distributed Time-critical Cloud Applications , 2016 .

[11]  Sateesh Addepalli,et al.  Fog computing and its role in the internet of things , 2012, MCC '12.

[12]  Vlado Stankovski,et al.  SWITCH-ing from Multi-Tenant to Event-Driven Videoconferencing Services , 2017, 2017 IEEE 2nd International Workshops on Foundations and Applications of Self* Systems (FAS*W).

[13]  Cees T. A. M. de Laat,et al.  A Software Workbench for Interactive, Time Critical and Highly Self-Adaptive Cloud Applications (SWITCH) , 2015, 2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing.

[14]  Dana Petcu,et al.  Developing a Model Driven Approach for engineering applications based on mOSAIC , 2013, Cluster Computing.

[15]  Yashuai Li,et al.  Web-based construction waste estimation system for building construction projects , 2013 .

[16]  Xin Guo,et al.  Applied Research on Tower Crane Safety Supervising System Based on Internet of Things , 2012 .

[17]  Minghe Yu,et al.  An RFID electronic tag based automatic vehicle identification system for traffic iot applications , 2011, 2011 Chinese Control and Decision Conference (CCDC).

[18]  Tomohiro Yoshida,et al.  Application of RFID technology to prevention of collision accident with heavy equipment , 2010 .

[19]  Rodrigo Roman,et al.  Mobile Edge Computing, Fog et al.: A Survey and Analysis of Security Threats and Challenges , 2016, Future Gener. Comput. Syst..

[20]  Nathan R. Swain,et al.  A review of open source software solutions for developing water resources web applications , 2015, Environ. Model. Softw..

[21]  Mani Golparvar-Fard,et al.  Automated Progress Monitoring Using Unordered Daily Construction Photographs and IFC-Based Building Information Models , 2015, J. Comput. Civ. Eng..

[22]  Žiga Turk,et al.  Component based engineering of a mobile BIM-based Augmented Reality system , 2014 .

[23]  Rajkumar Buyya,et al.  A data-centric framework for development and deployment of Internet of Things applications in clouds , 2015, 2015 IEEE Tenth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP).

[24]  Ludger Evers,et al.  A software tool for the spatiotemporal analysis and reporting of groundwater monitoring data , 2014, Environ. Model. Softw..

[25]  Uwe Stilla,et al.  A concept for automated construction progress monitoring using BIM-based geometric constraints and photogrammetric point clouds , 2015, J. Inf. Technol. Constr..

[26]  Soungho Chae.  Development of Warning System for Preventing Collision Accident on Construction Site , 2009 .

[27]  Jacques Marsot,et al.  Preventing plant-pedestrian collisions: Camera & screen systems and visibility from the driving position , 2016 .

[28]  Yacine Rezgui,et al.  Cloud computing for the architecture, engineering & construction sector: requirements, prototype & experience , 2013, Journal of Cloud Computing: Advances, Systems and Applications.

[29]  Hung-Ming Chen,et al.  A cloud-based system framework for performing online viewing, storage, and analysis on big data of massive BIMs , 2016 .

[30]  Yu-Cheng Lin,et al.  Dynamic mobile RFID-based supply chain control and management system in construction , 2007, Adv. Eng. Informatics.

[31]  Chimay J. Anumba,et al.  Smart Construction Objects , 2016, J. Comput. Civ. Eng..

[32]  Seokyon Hwang,et al.  Ultra-wide band technology experiments for real-time prevention of tower crane collisions , 2012 .

[33]  Marimuthu Palaniswami,et al.  An Information Framework for Creating a Smart City Through Internet of Things , 2014, IEEE Internet of Things Journal.

[34]  Quanyuan Feng,et al.  RFID technology and its applications in Internet of Things (IoT) , 2012, 2012 2nd International Conference on Consumer Electronics, Communications and Networks (CECNet).

[35]  Sylvain Kubler,et al.  Opportunities for enhanced lean construction management using Internet of Things standards , 2016 .

[36]  Chan-Sik Park,et al.  A social network system for sharing construction safety and health knowledge , 2014 .

[37]  Qun Li,et al.  A Survey of Fog Computing: Concepts, Applications and Issues , 2015, Mobidata@MobiHoc.

[38]  Zifeng Wu,et al.  Real-Time Anticollision System for Mobile Cranes during Lift Operations , 2015 .

[39]  Chimay J. Anumba,et al.  Cyber-physical systems for temporary structure monitoring , 2016 .

[40]  George Zillante,et al.  Mobile Internet based construction supply chain management: A critical review , 2016 .

[41]  Changyoon Kim,et al.  On-site construction management using mobile computing technology , 2013 .