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The goal of this project is to utilize, analyze and store multiple streams of raster & vector location related data, to create a multi-modal remote sensing platform for Louisville Metro Government.

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Project Cynefin

Cynefin is a Welsh word meaning haunt, habitat, acquainted, accustomed, familiar. It carries with it a sense of rootedness--temporal, physical, cultural or spiritual. The word is similar in meaning to Heimat in German and has been compared to the Maori word turangawaewae, a place to stand. The idea of the Cynefin framework is that it offers decision-makers a "sense of place" from which to view their perceptions.


Brief

The goal of this project is to utilize, analyze and store multiple streams of raster & vector location related data, to create a multi-modal remote sensing platform for Louisville Metro Government.

Immediate Enterprise Use Cases

There are any number of use cases for leveraging image-related data within a governmental body. This Innovation Project not only leverages existing or low cost commodity hardware for remote sensing & data collection, it also proves that low cost and intelligent smart city technology is in the reach of most cities.

  • General: Environmental GIS data capture

  • General: Built Environment Analytics

  • General: Vehicle Make/Model Analytics

  • Public Safety: Real Time Crime Center

  • Public Works: Asset Identification & Cataloging

  • Traffic: Flow & Usage Analysis

  • Predictive Pavement Condition

  • PARC: Enforcement

  • Sustainability: Tree Identification

  • Air Pollution Control District: Vehicle Make/Model Analytics for Pollution

Example Uses Cases

Mapillary

Data Sources

KYTC

KYTC has a photolog viewer from their asset collection vehicles. I believe they run interstates once a year and state routes every 2. Chad Shive ([email protected]) is the engineer over that program but it appears Jason Watson is the Technician that oversees it.

https://transportation.ky.gov/Maintenance/Pages/Pavement-Data-Collection.aspx

http://roadview-images.kytc.ky.gov/Van3_Mandli_Data_6/03-23-2017/2017_V3_100-KY-2298N/2017_V3_100-KY-2298N/Front/Dir_000/F_00001.jpg

http://maps.kytc.ky.gov/photolog/?config=Photolog&x1=5114935.986383551&y1=3868453.589951066&x2=5427435.986383551&y2=3971969.214951066&MODE=PL


Long Term Integration Phases

Proof of Concept

  • Commodity based modified hardware

    • Yi 4K Action Camera

Public Safety Pilot

Real Time Crime Center Axis camera integration

Phase 1

  • Existing Public Safety video sensor network (potential DeepLens hook?)
  • Drone imagery

Phase 2

  • Axon (Taser) video sensors
  • Multiple LIDAR sources

Technical Considerations


Process Flow


Long Term Maintenance & Requirements


Architecture

Metro Assets

Amazon Web Services

  • S3 block storage

  • Machine learning services

    • Amazon SageMaker (build ML training models)
    • Amazon Rekognition

SaaS (Software as a Service, cloud based)


Costs


Labor

SaaS (Software as a Service, cloud based)

OpenALPR

Requests Cost
2,000 Free
50,000 $49/month
250,000 $195
2,000,000 $995

Mapillary

Requests Cost
50,000 Free
500,000 $250
500,000 Contact

Available Grants & Funding Strategies


Policy


Privacy

Retention


Definitions

Remote sensing

GIS

LIDAR

AWS

Machine Learning


About

The goal of this project is to utilize, analyze and store multiple streams of raster & vector location related data, to create a multi-modal remote sensing platform for Louisville Metro Government.

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