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Artificial Intelligence Risk Assessment using Microsoft Azure Cognitive Services

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Rob Eby

Team 4 presented on using AI and cognitive services to assess risk from photographs of cable environments. The current app uses mobile devices to take photos and send them to a storage folder, then a web app interface uses cognitive services on Azure to analyze the photos and return results in real time. Future enhancements may include a database, logic apps, and other improvements to the architecture. The demo showed proof of concept for assisting safety inspections through automated image analysis.

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Azure Government Hackfest 2018 Team 4 AI Assisted Risk Assessment using Microsoft Azure Cognitive Services
Team Members • Tony Anecito, Enterprise Solutions Architect, ECY • Dave Cain, Sr Lead Developer, L&I • Mike Conley, Enterprise Applications Architect, L&I • Rob Eby, Enterprise Technology Architect, L&I • Phil Gardner, Solutions Architect Developer, L&I • Michael Mock, Services Development Technology Lead, L&I • Russ Robinson, DevOps Architect, L&I
AI Assisted Risk Assessment using Cognitive Services • Using AI and cognitive services to determine cable tripping hazards determining a safe condition vs a dangerous condition using photographs of the environment stored within a photo library. • Key elements of the project • Mobile devices (users) • Storage (folder) • Cognitive Services • Photos of Safe Areas or Hazardous Areas (cables) • Current app version is reporting in ‘real time’ back to the user with future enhancements.
Mobile devices Storage (Folder) Web App Cognitive Services Azure Cloud Users Current Architecture Send
Web app interface
Results
Photo library
Testing results
App Live Demo •http://riskassess.azurewebsites.us/
Mobile devices storageWeb App Cognitive Services Azure Cloud Users Future Architecture Logic App Upload
Project Summary and Findings •Due to time constraints simple architecture model was used for the “real time” identification of good/safe and bad/dangerous environments. •A simple folder was the data store to hold the pictures. •Future versions will include Database services, Logic App and other enhancements.
Q & A • Questions???

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Artificial Intelligence Risk Assessment using Microsoft Azure Cognitive Services

  • 1. Azure Government Hackfest 2018 Team 4 AI Assisted Risk Assessment using Microsoft Azure Cognitive Services
  • 2. Team Members • Tony Anecito, Enterprise Solutions Architect, ECY • Dave Cain, Sr Lead Developer, L&I • Mike Conley, Enterprise Applications Architect, L&I • Rob Eby, Enterprise Technology Architect, L&I • Phil Gardner, Solutions Architect Developer, L&I • Michael Mock, Services Development Technology Lead, L&I • Russ Robinson, DevOps Architect, L&I
  • 3. AI Assisted Risk Assessment using Cognitive Services • Using AI and cognitive services to determine cable tripping hazards determining a safe condition vs a dangerous condition using photographs of the environment stored within a photo library. • Key elements of the project • Mobile devices (users) • Storage (folder) • Cognitive Services • Photos of Safe Areas or Hazardous Areas (cables) • Current app version is reporting in ‘real time’ back to the user with future enhancements.
  • 4. Mobile devices Storage (Folder) Web App Cognitive Services Azure Cloud Users Current Architecture Send
  • 10. Mobile devices storageWeb App Cognitive Services Azure Cloud Users Future Architecture Logic App Upload
  • 11. Project Summary and Findings •Due to time constraints simple architecture model was used for the “real time” identification of good/safe and bad/dangerous environments. •A simple folder was the data store to hold the pictures. •Future versions will include Database services, Logic App and other enhancements.
  • 12. Q & A • Questions???