Intelligent hazard identification: Dynamic visibility measurement of construction equipment operators

Struck-by fatalities involving heavy equipment such as trucks and cranes accounted for 24.6% of the fatalities between 1997-2007 in the construction industry. Limited visibility due to blind spots and travel in reverse direction are the primary causes of these fatalities. Blind spots are spaces surr...

Full description

Bibliographic Details
Main Author: Ray, Soumitry J.
Other Authors: DesRoches, Reginald
Language:en_US
Published: Georgia Institute of Technology 2014
Subjects:
Online Access:http://hdl.handle.net/1853/51968
id ndltd-GATECH-oai-smartech.gatech.edu-1853-51968
record_format oai_dc
spelling ndltd-GATECH-oai-smartech.gatech.edu-1853-519682014-09-13T03:33:50ZIntelligent hazard identification: Dynamic visibility measurement of construction equipment operatorsRay, Soumitry J.Head posture estimationVehicle blindspotsProximitySafetyConstruction industryConstruction equipment Safety measuresStruck-by fatalities involving heavy equipment such as trucks and cranes accounted for 24.6% of the fatalities between 1997-2007 in the construction industry. Limited visibility due to blind spots and travel in reverse direction are the primary causes of these fatalities. Blind spots are spaces surrounding an equipment that are invisible to the equipment operator. Thus, a hazard is posed to the ground personnel working in the blind spaces of an equipment operator. This research presents a novel approach to intelligently identify potential hazards posed to workers operating near an equipment by determining the visible and blind space regions of an equipment operator in real-time. A depth camera is used to estimate the head posture of the equipment operator and continuously track the head location and orientation using Random Forests algorithm. The head posture information is then integrated with point cloud data of the construction equipment to determine both the visible and the blindspots region of the equipment operator using Ray-Casting algorithm. Simulation and field experiments were carried out to validate this approach in controlled and uncontrolled environment respectively. Research findings demonstrate the potential of this approach to enhance safety performance by detecting hazardous proximity situations.Georgia Institute of TechnologyDesRoches, Reginald2014-06-09T18:19:29Z2014-06-09T18:19:29Z2014-03-26Dissertationhttp://hdl.handle.net/1853/51968en_US
collection NDLTD
language en_US
sources NDLTD
topic Head posture estimation
Vehicle blindspots
Proximity
Safety
Construction industry
Construction equipment Safety measures
spellingShingle Head posture estimation
Vehicle blindspots
Proximity
Safety
Construction industry
Construction equipment Safety measures
Ray, Soumitry J.
Intelligent hazard identification: Dynamic visibility measurement of construction equipment operators
description Struck-by fatalities involving heavy equipment such as trucks and cranes accounted for 24.6% of the fatalities between 1997-2007 in the construction industry. Limited visibility due to blind spots and travel in reverse direction are the primary causes of these fatalities. Blind spots are spaces surrounding an equipment that are invisible to the equipment operator. Thus, a hazard is posed to the ground personnel working in the blind spaces of an equipment operator. This research presents a novel approach to intelligently identify potential hazards posed to workers operating near an equipment by determining the visible and blind space regions of an equipment operator in real-time. A depth camera is used to estimate the head posture of the equipment operator and continuously track the head location and orientation using Random Forests algorithm. The head posture information is then integrated with point cloud data of the construction equipment to determine both the visible and the blindspots region of the equipment operator using Ray-Casting algorithm. Simulation and field experiments were carried out to validate this approach in controlled and uncontrolled environment respectively. Research findings demonstrate the potential of this approach to enhance safety performance by detecting hazardous proximity situations.
author2 DesRoches, Reginald
author_facet DesRoches, Reginald
Ray, Soumitry J.
author Ray, Soumitry J.
author_sort Ray, Soumitry J.
title Intelligent hazard identification: Dynamic visibility measurement of construction equipment operators
title_short Intelligent hazard identification: Dynamic visibility measurement of construction equipment operators
title_full Intelligent hazard identification: Dynamic visibility measurement of construction equipment operators
title_fullStr Intelligent hazard identification: Dynamic visibility measurement of construction equipment operators
title_full_unstemmed Intelligent hazard identification: Dynamic visibility measurement of construction equipment operators
title_sort intelligent hazard identification: dynamic visibility measurement of construction equipment operators
publisher Georgia Institute of Technology
publishDate 2014
url http://hdl.handle.net/1853/51968
work_keys_str_mv AT raysoumitryj intelligenthazardidentificationdynamicvisibilitymeasurementofconstructionequipmentoperators
_version_ 1716714088307884033