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Increasing Solid Waste Collection Efficiency Through GIS

Increasing Solid Waste Collection Efficiency Through GIS

Presented by:
Bobby Kivett

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Transcript

  1. Increasing Solid Waste Collection Efficiency Through GIS Real ROI A

    Client Case Study for Mobile Applications & Process Enhancement Presented by: Bobby Kivett Former Public Works Director City of Asheboro, NC
  2.   •  Who is capturing the data? •  How accurate

    is that information? •  What are the deployment challenges? •  How do I access the data? •  How accurate is the geospatial location? Ques&ons  /  Concerns  about  Mobile  Technology?     Taking Data Collection to the Next Level – Start at the Beginning
  3. Story Time – Taking My Son Fishing Redbreast Sunfish (Lepomis

    auritus) Also Known As Long Ear, Panfish, Brim, or Bream
  4. Largemouth Bass (Micropterus salmoides) Also Known As black bass, oswego

    bass, dark bass, leaping larry bass, green trout, bigmouth bass, cave mouth, brikenbaker bass, lineside bass, bucketmouth or skeeterfish Story Time – Taking My Son Fishing
  5. •  ArcGIS Runtime SDKs •  Google Map & Navigation • 

    AutoCAD WS •  Mobile311 Examples of Mobile Technology
  6. Reduce Field Operations Costs Fuel Cost Vehicle Maintenance Man-hours Provide

    Quality Service Improve Efficiency Goals Mobile311 – Asheboro Solid Waste Case Study
  7. Automated trash drivers collect real time data that automatically creates

    work orders for: • Bulky Items • Yard Waste • Construction Debris • Other (water leaks, potholes, etc.)
  8. Prior to Technology Implementation $100 / hour operation costs 4

    Automated Solid Waste Trucks 2 Bulky Item Trucks 3 Yard Waste Trucks 5 days a week 8 hour days Mobile311 – Asheboro Solid Waste Case Study Annual Operation Cost $1,872,000
  9. Prior to Technology Implementation $100 / hour operation costs 4

    Automated Solid Waste Trucks 1 Bulky Item Truck 2 Yard Waste Trucks 4 days a week 6 hour days Mobile311 – Asheboro Solid Waste Case Study 36% Operations Reduction Annual Operation Cost $1,206,400
  10.   •  Who is capturing the data? •  Anyone in

    the field •  How accurate is that information? •  Button based with domains •  What are the deployment challenges? •  Easily deployed and managed remotely •  How do I access the data? •  SaaS Model means no software to maintain •  How accurate is the geospatial location? •  Generally 2 meters, but can be hand placed Ques&ons  /  Concerns  about  Mobile  Technology?     Taking Data Collection to the Next Level – Start at the Beginning