Liwaiwai Liwaiwai
  • /
  • Artificial Intelligence
  • Machine Learning
  • Robotics
  • Engineering
    • Architecture
    • Design
    • Software
    • Hybrid Cloud
    • Data
  • Learning
  • About
  • /
  • Artificial Intelligence
  • Machine Learning
  • Robotics
  • Engineering
    • Architecture
    • Design
    • Software
    • Hybrid Cloud
    • Data
  • Learning
  • About
Liwaiwai Liwaiwai
  • /
  • Artificial Intelligence
  • Machine Learning
  • Robotics
  • Engineering
    • Architecture
    • Design
    • Software
    • Hybrid Cloud
    • Data
  • Learning
  • About
  • Artificial Intelligence
  • Machine Learning

Using Machine Learning To Improve Road Maintenance

  • January 14, 2021
  • liwaiwai.com

There’s a new way to look out for potholes in the road and it doesn’t involve better eyeglasses or dispatching costly repair crews. Bus-mounted cameras and machine learning can do it for you, as the City of Memphis discovered.

Staying on top of deteriorating roads when you can’t add more personnel is a never ending cycle of patching holes as increasing traffic only worsens the problem.


Partner with liwaiwai.com
for your next big idea.
Let us know here.



From our partners:

CITI.IO :: Business. Institutions. Society. Global Political Economy.
CYBERPOGO.COM :: For the Arts, Sciences, and Technology.
DADAHACKS.COM :: Parenting For The Rest Of Us.
ZEDISTA.COM :: Entertainment. Sports. Culture. Escape.
TAKUMAKU.COM :: For The Hearth And Home.
ASTER.CLOUD :: From The Cloud And Beyond.
LIWAIWAI.COM :: Intelligence, Inside and Outside.
GLOBALCLOUDPLATFORMS.COM :: For The World's Computing Needs.
FIREGULAMAN.COM :: For The Fire In The Belly Of The Coder.
ASTERCASTER.COM :: Supra Astra. Beyond The Stars.
BARTDAY.COM :: Prosperity For Everyone.

Google Cloud Partner, SpringML worked with the City of Memphis to tackle this problem, assisting in repairing 63,000 potholes in one year, a massive improvement in pothole detection over previous manual efforts.

Advances in analytics and machine learning are making it possible for authorities to not only fix roads faster but actually prevent damage from occurring in the first place.

Memphis Area Transit Authority bus.jpg
Memphis Area Transit Authority bus

 

Using machine learning for road maintenance

The City of Memphis struggled with a problem many cities have to face: the continuous degradation of paved roads and the formation, through usage and weather, of potholes. These gaps in the road not only frustrate drivers, they slow down traffic, delaying commutes and mass transit, and they lead to greater wear and tear on vehicles. They’re just no good.

Potholes are inevitable, so the challenge for Memphis, and other cities, becomes how to keep up, putting repair resources where they can be most helpful. With limited hardware and staff, they can’t tackle every report from citizens. And those public reports don’t always present a full picture of the problem either.

Enter SpringML, who partners with public sector customers to solve problems with technology in creative ways. As the SpringML team joined with Memphis to figure this out, they first looked at what sorts of data they could get access to. And voila: bus cameras!

Read More  A Closer Look At Translation Hub: Enterprise Translation Made Easy

“Look for data you already have that can fuel your decision making, before you go out and try to acquire new data sets.” Eric Clark, AI Practice, SpringML

The city buses in Memphis all have front-mounted cameras, gathering data the entire time that the bus is running, mostly for traffic purposes. Every bus in the city was watching the roads every day!

Immediately the team had a treasure trove of data: every road covered by the mass transit system has daily recordings being captured. The bus routes are well defined and each bus has GPS to help correlate the footage with precise locations. The team set to work.

At the end of the day they retrieved videos from each bus and uploaded them to on-prem storage —a fairly manual process.

Downloading the video data manually from drives that were on the buses.jpg
Downloading the video data manually from drives that were on the buses
Bus system IT rack.jpg
Bus system IT rack, tracking location and camera data as it travels its route

Then a script checked for new files in the video directory nightly, and uploaded the new videos to Google Cloud Storage, to begin processing.

From there the Google Cloud Video Intelligence API could start to work, running its detection model on the new videos to look for possible pothole images. To make the initial pothole detection AI model the SpringML team took existing images and manually picked out potholes. They also used data from higher quality cameras to improve detection and accuracy of the model, and continued to feed new data from the bus routes to improve the model over time.

Results from the Video Intelligence model inference were sent to BigQuery, where the images, annotations, file metadata, location and scoring were kept and easily sorted or queried.

Read More  Checks, Google’s AI-Powered Privacy Platform
data from the BigQuery model.jpg
Some of the data from the BigQuery model, as it outputs pothole location and severity
Application used by public works employees to evaluate potholes.jpg
Application used by public works employees to evaluate potholes

The custom web-app presented possible potholes to public works employees, who could help correct the model when it made mistakes (frequently caused by stains, shadows or animals), or confirm a pothole and then trigger the next automated flow. Once a pothole is detected and confirmed, the team needs a work ticket to track the actual repair. So the web-app submits information about confirmed potholes to the city’s 311 information system, which can then generate a ticket, which will dispatch a work crew and repair vehicle to actually repair the road.

The full process of pothole data collection and detection.jpg
The full process of pothole data collection and detection

A smooth road ahead

As well as detecting and fixing potholes faster, this effort has paved the way for future projects that can improve public infrastructure, as more of the data gets gathered and applied to decision making.

Want to learn more? Read this Video Intelligence API quickstart to try it out. Listen to the interview with SpringML’s Eric Clark on the GCP Podcast, and check out more machine learning tools in our AI Platform.

 

By Max Saltonstall Developer Advocate, Google Cloud, Google Cloud | Eric Clark AI Practice, SpringML
Source Google Cloud


For enquiries, product placements, sponsorships, and collaborations, connect with us at [email protected]. We'd love to hear from you!

Our humans need coffee too! Your support is highly appreciated, thank you!

liwaiwai.com

Related Topics
  • BigQuery
  • Google AI
  • Google Cloud
  • SpringML
You May Also Like
OpenAI
View Post
  • Artificial Intelligence
  • Platforms

How We Interact With Information: The New Era Of Search

  • September 28, 2023
View Post
  • Artificial Intelligence
  • Engineering
  • Machine Learning
  • Platforms

Bring AI To Looker With The Machine Learning Accelerator

  • September 28, 2023
View Post
  • Artificial Intelligence
  • Technology

Microsoft And Mercy Collaborate To Empower Clinicians To Transform Patient Care With Generative AI

  • September 27, 2023
View Post
  • Artificial Intelligence
  • Technology

NASA’s Mars Rovers Could Inspire A More Ethical Future For AI

  • September 26, 2023
View Post
  • Artificial Intelligence
  • Platforms

Oracle CloudWorld 2023: 6 Key Takeaways From The Big Annual Event

  • September 25, 2023
View Post
  • Artificial Intelligence

3 Ways AI Can Help Communities Adapt To Climate Change In Africa

  • September 25, 2023
Robotic Hand | Lights
View Post
  • Artificial Intelligence
  • Technology

Nvidia H100 Tensor Core GPUs Come To Oracle Cloud

  • September 24, 2023
View Post
  • Artificial Intelligence
  • Engineering
  • Technology

AI-Driven Tool Makes It Easy To Personalize 3D-Printable Models

  • September 22, 2023
A Field Guide To A.I.
Navigate the complexities of Artificial Intelligence and unlock new perspectives in this must-have guide.
Now available in print and ebook.

charity-water



Stay Connected!
LATEST
  • OpenAI 1
    How We Interact With Information: The New Era Of Search
    • September 28, 2023
  • 2
    Bring AI To Looker With The Machine Learning Accelerator
    • September 28, 2023
  • 3
    3 Questions: A New PhD Program From The Center For Computational Science And Engineering
    • September 28, 2023
  • 4
    Microsoft And Mercy Collaborate To Empower Clinicians To Transform Patient Care With Generative AI
    • September 27, 2023
  • 5
    NASA’s Mars Rovers Could Inspire A More Ethical Future For AI
    • September 26, 2023
  • 6
    Oracle CloudWorld 2023: 6 Key Takeaways From The Big Annual Event
    • September 25, 2023
  • 7
    3 Ways AI Can Help Communities Adapt To Climate Change In Africa
    • September 25, 2023
  • Robotic Hand | Lights 8
    Nvidia H100 Tensor Core GPUs Come To Oracle Cloud
    • September 24, 2023
  • 9
    AI-Driven Tool Makes It Easy To Personalize 3D-Printable Models
    • September 22, 2023
  • 10
    Huawei: Advancing a Flourishing AI Ecosystem Together
    • September 22, 2023

about
About
Hello World!

We are liwaiwai.com. Created by programmers for programmers.

Our site aims to provide materials, guides, programming how-tos, and resources relating to artificial intelligence, machine learning and the likes.

We would like to hear from you.

If you have any questions, enquiries or would like to sponsor content, kindly reach out to us at:

[email protected]

Live long & prosper!
Most Popular
  • Coffee | Laptop | Notebook | Work 1
    First HP Work Relationship Index Shows Majority of People Worldwide Have an Unhealthy Relationship with Work
    • September 20, 2023
  • 2
    Huawei Connect 2023: Accelerating Intelligence For Shared Success
    • September 20, 2023
  • 3
    Applying Generative AI To Product Design With BigQuery DataFrames
    • September 21, 2023
  • 4
    Combining AI With A Trusted Data Approach On IBM Power To Fuel Business Outcomes
    • September 21, 2023
  • Microsoft and Adobe 5
    Microsoft And Adobe Partner To Deliver Cost Savings And Business Benefits
    • September 21, 2023
  • /
  • Artificial Intelligence
  • Explore
  • About
  • Contact Us

Input your search keywords and press Enter.