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Automated Risk Assessment from Video Data: Integrating Open Resources

Implement a protocol using video analysis techniques to assess road risk factors in developing countries, leveraging deep learning for automation. Utilize commodity hardware and open data resources. Apply similar techniques for health data analysis. In the realm of CRM and marketing, enrich customer databases with social behavior profiling for personalized advertising. Explore Bayesian models for consistent probability evaluation. Interface via web dashboards for optimal marketing decisions while respecting privacy regulations.

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Automated Risk Assessment from Video Data: Integrating Open Resources

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  1. Risk assessment from video data Risk assessment from video data KEY ASPECTS • Riskassessment on roads(focus on developingcountries) • Exploit video analysistechinques • Integrate open data resources

  2. Risk assessment from video data Risk assessment from video data • Goals: • Define a protocol to assess risk factors in roads from video images and open data. • Use commodity hardware as much as possible. • Maximize automation of the procedure. 3. Assessrisklevel on portions of thechosen road (green, yellow, orange,red & black) 2. Build a score by combining thedifferentvalues of indicators 1. Identifyriskindicatorsthat can be evaluatedwith (almost) no human intervention

  3. Risk assessment from video data Risk assessment from video data Camera videos + GPS RoadLabPro app (for road pavement condition) OpenStreetMap maps + metadata(for crossroads and road area)

  4. Risk assessment from video data Risk assessment from video data Deeplearning + image analysistechniquesallow to detect the presence of persons and road signs… …butalso road lines tosome extent (and from thosethe curvature of the road)

  5. The resulthasbeen a tool to make the dataprocessing mostlyautomated: videos are uploaded, together with some manualmetadata(name of the road, some camera calibrationparams, etc.) and the riskanalysisisperformed. Risk assessment from video data Risk assessment from video data

  6. Video data and health Video data and health Similartechniqueshavebeenused in healthcarecontext Component 1: find in a movie thepresence and the position ofhuman faces (OpenCV library) Component 2: extract heartbeatsfrom variations of the red channelinside the boxed areas of the image. + Component 3: detect anomaliesin the heartbeat frequency and recognize disease “footprints” +

  7. CRM and marketing CRM and marketing KEY ASPECTS • EnrichcustomerDBs • Social “behavior” profiling • Choosingcampaigns and contactchannel per-customer

  8. CRM and marketing CRM and marketing • Goals: • Acknowledge that digital connections and social networks have de facto changed completely face to marketing actions towards customers. • Replace traditional campaigns with customized advertising based on customer habits. • Exploit all available info (in the limit of privacy laws!) about single customers and similar profiles to find what products can be of interest.

  9. CRM and marketing CRM and marketing … … name address job health salary real estatemarket activitieson brand pages activities on competitor pages customer info goal info context info via customer segments(age, geo, etc.) OPEN DATA

  10. CRM and marketing CRM and marketing Bayesianmodelscan synthetizealldifferent data sources in a consistentprobabilityevaluation of NBP. TOUCHPOINT LIFE CYCLE CUSTOMERINFO SOCIAL ACTIVITIES PASTPRODUCTS NEXT BEST PRODUCT An userinterfacethrough web dashboardsallowsCRM decisionmakers to choose the mostconvenient marketing activity in each area. For privacy reasonalldisplayed data are simulated.

  11. Furtherapplications Furtherapplications % % Similartechniqueshavebeenused in otherproblemsrelated to profiling Prob manutenzionepredittiva frodi, churn, ecc.

  12. Thankyou for yourattention

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