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A rule-based methodology for automated progress monitoring of construction activities: A case for masonry work

Title	A rule-based methodology for automated progress monitoring of construction activities: A case for masonry work
Author	Işın, Gürşans Güven, Ergen, E.
Publication Date:	2019
Publication Place	- International Council for Research and Innovation in Building and Construction
Subject	Automated progress monitoring, Equipment tracking, Domain-heuristics, Data fusion, Sensor-based technologies
Type	Periodical
Language	English
Digital	Yes
Manuscript	No
Library:	Özyeğin University
Library Asset ID	1874-4753
Record ID	a20c380e-877d-4595-8cc1-29ac01202747
Library Location	Civil Engineering
Date	2019
Notes	TÜBİTAK
Sample Text	The conventional approach that is used to monitor construction projects is to collect progress data from the construction site through visual investigation. This results in deficient and sometimes erroneous data, and leads to inefficiencies in project control, delays and cost overruns. To address these problems in building construction projects, an approach was developed to automatically monitor activity progress by tracking major construction equipment and bulk materials using sensor-based technologies that are cost-effective and easy to deploy. In this approach data obtained from sensors (e.g., load sensor) and/or other sensor-based technologies (i.e., Radio Frequency Identification (RFID)), which were deployed on major construction resources, were fused using rule-based algorithms to determine the activity progress. This progress data was compared with human-generated site related data (e.g., schedules, site reports) to determine the activity performance. This paper presents the developed data fusion approach and rule-based data fusion algorithms that incorporate the domain-specific heuristic information for determining the activity's overall progress. To validate the proposed approach, a proof-of-concept prototype was deployed and tested at a construction site for monitoring the progress of masonry work. The results show that the developed approach achieved 95% average accuracy in identifying the progress of the masonry work that was monitored during the field tests. The main contributions of this study are the rule-based data fusion approach and the rules that were developed for processing data from equipment and bulk materials. These rules can be used to determine the progress of other activities that use similar resources.
Cilt	24

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A rule-based methodology for automated progress monitoring of construction activities: A case for masonry work

Author Işın, Gürşans Güven, Ergen, E.

Publication Date 2019

Publication Place - International Council for Research and Innovation in Building and Construction

Subject Automated progress monitoring, Equipment tracking, Domain-heuristics, Data fusion, Sensor-based technologies

Type Periodical

Language English

Digital Yes

Manuscript No

Library Özyeğin University

Library Asset ID 1874-4753

Record ID a20c380e-877d-4595-8cc1-29ac01202747

Library Location Civil Engineering

Date 2019

Notes TÜBİTAK

Sample Text The conventional approach that is used to monitor construction projects is to collect progress data from the construction site through visual investigation. This results in deficient and sometimes erroneous data, and leads to inefficiencies in project control, delays and cost overruns. To address these problems in building construction projects, an approach was developed to automatically monitor activity progress by tracking major construction equipment and bulk materials using sensor-based technologies that are cost-effective and easy to deploy. In this approach data obtained from sensors (e.g., load sensor) and/or other sensor-based technologies (i.e., Radio Frequency Identification (RFID)), which were deployed on major construction resources, were fused using rule-based algorithms to determine the activity progress. This progress data was compared with human-generated site related data (e.g., schedules, site reports) to determine the activity performance. This paper presents the developed data fusion approach and rule-based data fusion algorithms that incorporate the domain-specific heuristic information for determining the activity's overall progress. To validate the proposed approach, a proof-of-concept prototype was deployed and tested at a construction site for monitoring the progress of masonry work. The results show that the developed approach achieved 95% average accuracy in identifying the progress of the masonry work that was monitored during the field tests. The main contributions of this study are the rule-based data fusion approach and the rules that were developed for processing data from equipment and bulk materials. These rules can be used to determine the progress of other activities that use similar resources.

Cilt 24