By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    data-driven white label SEO
    Does Data Mining Really Help with White Label SEO?
    7 Min Read
    marketing analytics for hardware vendors
    IT Hardware Startups Turn to Data Analytics for Market Research
    9 Min Read
    big data and digital signage
    The Power of Big Data and Analytics in Digital Signage
    5 Min Read
    data analytics investing
    Data Analytics Boosts ROI of Investment Trusts
    9 Min Read
    football data collection and analytics
    Unleashing Victory: How Data Collection Is Revolutionizing Football Performance Analysis!
    4 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-23 SmartData Collective. All Rights Reserved.
Reading: New Deep Learning Systems Profoundly Disrupt Fleet Management Operations
Share
Notification Show More
Aa
SmartData CollectiveSmartData Collective
Aa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Exclusive > New Deep Learning Systems Profoundly Disrupt Fleet Management Operations
Machine Learning

New Deep Learning Systems Profoundly Disrupt Fleet Management Operations

Deep learning is having a profound impact on the future of fleet management through greater efficiency.

Ryan Kh
Last updated: 2021/06/20 at 5:19 PM
Ryan Kh
6 Min Read
deep learning in fleet management
Shutterstock Photo License - By Scharfsinn
SHARE

Deep learning tech is influencing and enhancing many industries, promising to provide insights into key business operations which were not previously possible to unearth. Transportation and logistics is a prime example.

Contents
Improvements to efficiency & sustainabilityRoute adjustments made in real timeMaintenance issues avoided entirelyUnpacking drivers’ bad habits

The transportation analytics industry is projected to be worth $27 billion by 2026. One of the biggest applications of this technology lies with using deep learning to streamline fleet management.

Fleet management is one area that is especially well positioned to benefit from the latest data-driven analytical tools, so here is a look at just how much positive disruption is being caused in this market at the moment.

Improvements to efficiency & sustainability

Businesses which operate fleets of vehicles, whether small or large, are under increased scrutiny with regards to the sustainability of their operations at the moment.

More Read

companies using big data to address distracted driving

Car and Mobile Companies Use Big Data to Reduce Distracted Driving

How Big Data Has Become Integral to Commercial Fleet Success
Fleet Management and Big Data: Points to Consider

There are a number of ways to go about improving the eco-friendliness of business fleets, with the long term aim of many organizations being to migrate to fully electric vehicles, leaving fossil fuel powered incumbents in the past where they belong.

The problem with this is that ditching diesel-powered fleets to upgrade to EVs is expensive and often impractical in the short to medium term, which is where modern fleet management solutions with deep learning capabilities come into play.

Since it is possible to retrofit existing fleets with the GPS tracking and monitoring devices necessary to track everything from distance travelled to time spent idling, businesses can affordably tap into a wealth of data points, extrapolating actionable findings that can show where improvements to sustainability are achievable today, not tomorrow.

Route adjustments made in real time

Following on from the improved efficiency which is available through fairly basic vehicle monitoring and number-crunching, deep learning systems combined with fleet management software can also be put to work to solve the most common transport conundrum in history; congestion.

Systems can use a combination of GPS tracking in vehicles and access to traffic updates to determine the best route in real time, making changes as conditions shift from minute to minute, and ensuring that drivers are not unnecessarily held up by jams that could be avoided.

Rather than requiring a large team to constantly be monitoring and relaying this kind of information to drivers, or undergoing extensive analysis of routes to try and identify trouble spots and places where time savings could be made, deep learning takes all of this and automates it, giving fleet operators the insights they need in less time.

Maintenance issues avoided entirely

The measuring of various performance metrics within fleets can also extend to maintenance matters. Vehicles which suffer faults outside of scheduled periods of maintenance can create added costs for business and compromise customer satisfaction levels, as well as potentially putting drivers at risk.

Conversely, if deep learning is applied to information fed in from tens, hundreds or thousands of vehicles, the software can create maintenance models which give businesses a clearer picture of overall vehicle health, as well as an opportunity to carry out repairs at predetermined points which match real world driving conditions, not the claims made by manufacturers.

Once again it all comes down to giving decision-makers the power to come to informed conclusions about the factors impacting fleet productivity and overarching costs, without needing to invest vast amounts of time, money and resources into manually reaching these decisions.

Unpacking drivers’ bad habits

There are so many aspects of the way people drive vehicles that determine their overall performance behind the wheel, from the perspective of efficiency, productivity and of course safety.

In the past, businesses were unable to delve into the data on driver behavior in any meaningful way, other than tracking things like fuel costs and incident reports. However, deep learning is ushering in an era in which far more information can be gathered, while also being processable in real time, so that bad habits can be singled out and suggestions for changes provided on the fly.

As well as addressing all of the aforementioned issues, this has the added benefit of depersonalizing the process of training and coaching professional driving, taking the emotion out of recommending changes to habits so that they are more likely to comply.

In the long term, deep learning will bring about the age of fully autonomous business fleets, but until that happens on a large scale, it will remain crucial to making current fleet operations as effective and impactful as possible.

TAGGED: deep learning in fleet management, transportation analytics, transportation big data
Ryan Kh February 21, 2021
Share This Article
Facebook Twitter Pinterest LinkedIn
Share
By Ryan Kh
Follow:
Ryan Kh is an experienced blogger, digital content & social marketer. Founder of Catalyst For Business and contributor to search giants like Yahoo Finance, MSN. He is passionate about covering topics like big data, business intelligence, startups & entrepreneurship. Email: ryankh14@icloud.com

Follow us on Facebook

Latest News

sobm for ai-driven cybersecurity
Software Bill of Materials is Crucial for AI-Driven Cybersecurity
Security
IT budgeting for data-driven companies
IT Budgeting Practices for Data-Driven Companies
IT
machine,translation
Translating Artificial Intelligence: Learning to Speak Global Languages
Artificial Intelligence
data science upskilling
Upskilling for Emerging Industries Affected by Data Science
Big Data

Stay Connected

1.2k Followers Like
33.7k Followers Follow
222 Followers Pin

You Might also Like

companies using big data to address distracted driving
Big Data

Car and Mobile Companies Use Big Data to Reduce Distracted Driving

7 Min Read
big data in fleet management
Big Data

How Big Data Has Become Integral to Commercial Fleet Success

8 Min Read
big data in fleet management
Big Data

Fleet Management and Big Data: Points to Consider

6 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

ai in ecommerce
Artificial Intelligence for eCommerce: A Closer Look
Artificial Intelligence
AI and chatbots
Chatbots and SEO: How Can Chatbots Improve Your SEO Ranking?
Artificial Intelligence Chatbots Exclusive

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
Go to mobile version
Welcome Back!

Sign in to your account

Lost your password?