Drone-Assisted Inspection for Automated Accident Damage Estimation: A Deep Learning Approach

M. Adel Serhani, Tony T. Ng, Asma Al Falasi, Meera Al Saedi, Fatima Al Nuaimi, Hamda Al Shamsi, Al Damani Al Shamsi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Drones have been used in many application domains nowadays including traffic congestion control, weather information collection, disaster and rescue interventions, and surveillance operations. The drone adoption lies on their capabilities to collect images, videos as well as other sensory data from the air, stream this data to the cloud for processing, and analytics in order to derive important real-time decisions. In this paper, we propose a drone assisted inspection for accident damage estimation based on deep learning approach. Drones are automatically scheduled to visit the accident locations, and data is retrieved for further processing and analytics. We developed a two-phases damage estimation approach, where in the first phase we use deep learning approach to identify and classify objects from accident's images, and in the second phase we measure the size of damaged objects and we estimate the overall cost of the accident's damages. We evaluated our two-phase approach using data of various accidents, and the classification accuracy we have obtained vary between 0.79 and 0.94 and the accident's damage cost estimation most of time is 100% accepted by the expert.

Original languageEnglish
Title of host publicationICUFN 2019 - 11th International Conference on Ubiquitous and Future Networks
PublisherIEEE Computer Society
Pages682-687
Number of pages6
ISBN (Electronic)9781728113395
DOIs
Publication statusPublished - Jul 2019
Event11th International Conference on Ubiquitous and Future Networks, ICUFN 2019 - Zagreb, Croatia
Duration: Jul 2 2019Jul 5 2019

Publication series

NameInternational Conference on Ubiquitous and Future Networks, ICUFN
Volume2019-July
ISSN (Print)2165-8528
ISSN (Electronic)2165-8536

Conference

Conference11th International Conference on Ubiquitous and Future Networks, ICUFN 2019
Country/TerritoryCroatia
CityZagreb
Period7/2/197/5/19

Keywords

  • Damage inspection
  • classification
  • deep learning
  • drone
  • estimation
  • object image extraction
  • size measurement

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture

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