Proximity hazard indicator for workers-on-foot near miss interactions with construction equipment and geo-referenced hazard areas

Abstract Despite the many existing best practices in safety, the construction industry lacks automated safety monitoring and analysis of task-level construction operations. Data to workforce, equipment, and the overall site safety performance are currently observed, measured, and evaluated almost always manually. Such resulting performance information is likely assessed infrequently and due to subjective human interpretation or error. Research in lagging and leading safety indicators shows further that safety knowledge is hardly ever shared among relevant project stakeholders in time to prevent accidents. Since a large number of all construction fatalities are related to struck-by events – for example, workers-on-foot being too close to construction equipment and to other restricted or geo-referenced hazard areas – a novel framework around real-time location tracking technology was designed and tested to collect and study near miss data. The objectives of this article are to automatically identify the areas of static and dynamic hazards on a construction site and to automatically gather and analyze the spatial–temporal conflicts between workers-on-foot and the identified hazards. Automated conversion of raw sensor location data collected to the operation of workers, equipment, and geo-referenced hazard areas into meaningful proximity-related safety information is introduced. Field experiments validate the research based on an a priori created safe site layout information model. Results are in particular useful for practitioners or researchers who would like to enhance their quantitative and visual understanding of operational construction resource activity monitoring and analysis, and in the specific domain of detecting and mapping spatial–temporal proximity relationships of near miss events. Applications of the resulting knowledge are explained in the context of empowering construction safety engineers, managers, and the workforce by enhancing decision making in safe site layout design and planning and providing additional interactive tools in safety education and training.

[1]  Jimmie Hinze,et al.  Autonomous pro-active real-time construction worker and equipment operator proximity safety alert system , 2010 .

[2]  Aviad Shapira,et al.  Measurement and Risk Scales of Crane-Related Safety Factors on Construction Sites , 2009 .

[3]  Paul M. Goodrum,et al.  Assessing the impact of materials tracking technologies on construction craft productivity , 2009 .

[4]  Carlos H. Caldas,et al.  Real-Time Three-Dimensional Occupancy Grid Modeling for the Detection and Tracking of Construction Resources , 2007 .

[5]  Jochen Teizer,et al.  Mobile 3D mapping for surveying earthwork projects using an Unmanned Aerial Vehicle (UAV) system , 2014 .

[6]  Jochen Teizer,et al.  Automating the blind spot measurement of construction equipment , 2010 .

[7]  Mohamed Al-Hussein,et al.  Algorithm for Mobile Crane Walking Path Planning in Congested Industrial Plants , 2015 .

[8]  Mani Golparvar-Fard,et al.  Evaluation of image-based modeling and laser scanning accuracy for emerging automated performance monitoring techniques , 2011 .

[9]  Christian Koch,et al.  Three-Dimensional Tracking of Construction Resources Using an On-Site Camera System , 2012, J. Comput. Civ. Eng..

[10]  D. Fang,et al.  Why operatives engage in unsafe work behavior: Investigating factors on construction sites , 2008 .

[11]  Carlos H. Caldas,et al.  Framework for Real-Time Three-Dimensional Modeling of Infrastructure , 2005 .

[12]  Aviad Shapira,et al.  “Soft” Considerations in Equipment Selection for Building Construction Projects , 2007 .

[13]  Carl T. Haas,et al.  Multisensor data fusion for on-site materials tracking in construction , 2010 .

[14]  Burcu Akinci,et al.  Automating the task of tracking the delivery and receipt of fabricated pipe spools in industrial projects , 2006 .

[15]  Charles M. Eastman,et al.  Building Information Modeling (BIM) and Safety: Automatic Safety Checking of Construction Models and Schedules , 2013 .

[16]  Seokho Chi,et al.  Automated Object Identification Using Optical Video Cameras on Construction Sites , 2011, Comput. Aided Civ. Infrastructure Eng..

[17]  Eric Marks,et al.  Method for testing proximity detection and alert technology for safe construction equipment operation , 2013 .

[18]  Frédéric Bosché,et al.  Automated recognition of 3D CAD model objects in laser scans and calculation of as-built dimensions for dimensional compliance control in construction , 2010, Adv. Eng. Informatics.

[19]  Jochen Teizer,et al.  Cell-based construction site simulation model for earthmoving operations using real-time equipment location data , 2015 .

[20]  Gil Luria,et al.  The use of supervisory practices as leverage to improve safety behavior: a cross-level intervention model. , 2003, Journal of safety research.

[21]  Helen Lingard,et al.  Behavior-based safety management in Hong Kong's construction industry , 1997 .

[22]  Zhen-Zhong Hu,et al.  BIM- and 4D-based integrated solution of analysis and management for conflicts and structural safety problems during construction: 1. Principles and methodologies , 2011 .

[23]  Jochen Teizer,et al.  Ontology-based semantic modeling of construction safety knowledge: Towards automated safety planning for job hazard analysis (JHA) , 2015 .

[24]  Zhongke Shi,et al.  A performance evaluation of vision and radio frequency tracking methods for interacting workforce , 2011, Adv. Eng. Informatics.

[25]  Jun Wang,et al.  Geotechnical and safety protective equipment planning using range point cloud data and rule checking in building information modeling , 2015 .

[26]  Tao Cheng,et al.  Modeling Tower Crane Operator Visibility to Minimize the Risk of Limited Situational Awareness , 2014 .

[27]  Charles M. Eastman,et al.  Workforce location tracking to model, visualize and analyze workspace requirements in building information models for construction safety planning , 2015 .

[28]  Tao Cheng,et al.  Data Fusion of Real-Time Location Sensing and Physiological Status Monitoring for Ergonomics Analysis of Construction Workers , 2013, J. Comput. Civ. Eng..

[29]  Patricio A. Vela,et al.  Monocular Videogrammetry for Generating Absolute-Scale 3D Point Cloud Data of Civil and Infrastructure Scenes , 2013 .

[30]  Jochen Teizer,et al.  Coarse head pose estimation of construction equipment operators to formulate dynamic blind spots , 2012, Adv. Eng. Informatics.

[31]  Jimmie Hinze,et al.  Proactive Construction Safety Control: Measuring, Monitoring, and Responding to Safety Leading Indicators , 2013 .

[32]  T. Michael Toole,et al.  Construction Site Safety Roles , 2002 .

[33]  Burcu Akinci,et al.  Automatic Reconstruction of As-Built Building Information Models from Laser-Scanned Point Clouds: A Review of Related Techniques | NIST , 2010 .

[34]  A. Glendon,et al.  Human Safety and Risk Management, Second Edition , 2006 .

[35]  Todd M. Ruff.  Evaluation of Devices to Prevent Construction Equipment Backing Incidents , 2004 .

[36]  Mohamed Al-Hussein,et al.  Automated Method for Checking Crane Paths for Heavy Lifts in Industrial Projects , 2013 .

[37]  Burcu Akinci,et al.  Simulation-Based Identification of Possible Locations for Mobile Cranes on Construction Sites , 2008 .

[38]  Carlos H. Caldas,et al.  Human-Assisted Obstacle Avoidance System using 3D Workspace Modeling for Construction Equipment Operation , 2006 .

[39]  Berardo Naticchia,et al.  A proactive system for real-time safety management in construction sites , 2009 .

[40]  Juan Carlos Niebles,et al.  Vision-based action recognition of earthmoving equipment using spatio-temporal features and support vector machine classifiers , 2013, Adv. Eng. Informatics.

[41]  Zhongke Shi,et al.  Vision-Based Tower Crane Tracking for Understanding Construction Activity , 2014, J. Comput. Civ. Eng..

[42]  Jochen Teizer,et al.  Automatic spatio-temporal analysis of construction site equipment operations using GPS data , 2013 .

[43]  Patricio A. Vela,et al.  Performance evaluation of ultra wideband technology for construction resource location tracking in harsh environments , 2011 .

[44]  Jagdeep S. Chhokar,et al.  Improving safety through applied behavior analysis , 1984 .

[45]  Berardo Naticchia,et al.  Design and first development of an automated real‐time safety management system for construction sites , 2009 .

[46]  Jie Gong,et al.  Data processing for real-time construction site spatial modeling , 2008 .

[47]  Jia-Chong Du,et al.  3D laser scanning and GPS technology for landslide earthwork volume estimation , 2007 .

[48]  Seokho Chi,et al.  Image-Based Safety Assessment: Automated Spatial Safety Risk Identification of Earthmoving and Surface Mining Activities , 2012 .

[49]  Todd M Ruff,et al.  Preventing collisions involving surface mining equipment: a GPS-based approach. , 2003, Journal of safety research.

[50]  Tao Cheng,et al.  Automated task-level activity analysis through fusion of real time location sensors and worker's tho , 2013 .

[51]  Jochen Teizer,et al.  Automated Collection, Identification, Localization, and Analysis of Worker-Related Proximity Hazard Events in Heavy Construction Equipment Operation , 2015 .

[52]  Jimmie Hinze,et al.  AN EVALUATION OF SAFETY PERFORMANCE MEASURES FOR CONSTRUCTION PROJECTS , 2003 .

[53]  Dongping Fang,et al.  Factor analysis-based studies on construction workplace safety management in China , 2004 .

[54]  Roger V. Bostelman,et al.  Methods for improving visibility measurement standards of powered industrial vehicles , 2014 .

[55]  Jochen Teizer,et al.  Global Positioning System Data to Model and Visualize Workspace Density in Construction Safety Planning , 2015 .

[56]  Jochen Teizer,et al.  Visibility-related fatalities related to construction equipment , 2011 .

[57]  Tao Cheng,et al.  Real-time resource location data collection and visualization technology for construction safety and activity monitoring applications , 2013 .

[58]  Amr A. Oloufa,et al.  GPS-Based Wireless Collision Detection of Construction Equipment , 2002 .

[59]  Carl T. Haas,et al.  Multiple Heavy Lifts Optimization , 1996 .

[60]  Jochen Teizer,et al.  Computing 3D blind spots of construction equipment: Implementation and evaluation of an automated measurement and visualization method utilizing range point cloud data , 2013 .

[61]  Alexander Laufer,et al.  ASSESSMENT OF SAFETY PERFORMANCE MEASURES AT CONSTRUCTION SITES , 1986 .

[62]  Osama Moselhi,et al.  Integrating 3D laser scanning and photogrammetry for progress measurement of construction work , 2008 .

[63]  Jochen Teizer.  Wearable, wireless identification sensing platform: Self-Monitoring Alert and Reporting Technology for Hazard Avoidance and Training (SmartHat) , 2015, J. Inf. Technol. Constr..

[64]  Fernanda Leite,et al.  Exploring approaches to improve the performance of autonomous monitoring with imperfect data in location-aware wireless sensor networks , 2014, Adv. Eng. Informatics.

[65]  Charles M. Eastman,et al.  BIM-based fall hazard identification and prevention in construction safety planning , 2015 .

[66]  Patricio A. Vela,et al.  A Sparsity‐Inducing Optimization‐Based Algorithm for Planar Patches Extraction from Noisy Point‐Cloud Data , 2015, Comput. Aided Civ. Infrastructure Eng..

[67]  Roger V. Bostelman,et al.  Improved Methods for Evaluation of Visibility for Industrial Vehicles Towards Safety Standards , 2013 .

[68]  Jimmie Hinze,et al.  Safety Programs in Large Construction Firms , 1981 .