• Train

          Develop

          Deploy

          Operate

          Data Collection

          Building Blocks​

          Device Enrollment

          Monitoring Dashboards

          Video Annotation​

          Application Editor​

          Device Management

          Remote Maintenance

          Model Training

          Application Library

          Deployment Manager

          Unified Security Center

          AI Model Library

          Configuration Manager

          IoT Edge Gateway

          Privacy-preserving AI

          Ready to get started?

          Overview
          Whitepaper
          Expert Services
  • Services
        • Resources

          Research

          Company

          Why Viso Suite?

          The Viso Blog

          About Viso

          Evaluation Guide

          Explore Use Cases

          Support Center

          Viso Suite Whitepaper

          Industry Reports

          Careers

          Enterprise Features

          Technology Guides

          Contact

          No-code / Low-code

          Security & Trust

          Why Viso Suite

          The no-code platform for teams to build, deploy and scale computer vision applications in one solution. Viso Suite is trusted by Fortune 500 companies.

  • Pricing

Vehicle Dwell Time

Monitor the time vehicles spend at scheduled stops without moving to increase efficiency.

What is Vehicle Dwell Time Detection?

Computer Vision is used to automatically track the dwell time of vehicles in transportation use cases. In transportation, dwell time is the time a vehicle such as a public transit bus, train or car spends at a scheduled stop without moving. Dwell time is one of the most important metrics to measure the efficiency of public transport with the goal of keep waiting times as short as possible.

In supply chain management, dwell time is the time drivers spend at facilities waiting to drop off or pick up loads. Optimizing dwell time is a major challenge for stakeholders across the supply chain since it causes imbalanced load volumes, carrier arrival delays, and inefficient on-site operations. Such waiting times force trucks to wait for an empty loading dock to load or unload their goods. This has a significant environmental impact as drivers have to stay idle for long periods of time at the pickup or delivery facility.

Deep learning algorithms can detect and classify vehicles in public places by processing real-time video streams of surveillance cameras. Such a system determines if the vehicle is moving or stopped, and can automatically determine the dwell time in between stops.

How to Measure Dwell Time with Deep Learning

Real-time object detection for the identification and classification of different vehicles using the video stream of conventional cameras.

  • Detect specific vehicle types such as bus, train, metro, car, motorcycle, bicycle, truck, and more.
  • Detect the status for each identified vehicle (moving, at rest).
  • Focus recognition on specific areas within the camera images, for example, sidewalks, specific parking lots, and other.
  • Track the waiting time of vehicles over time and calculate key metrics to provide a performance score.
  • Monitor dwell time across multiple locations.

Value of Automated Vehicle Dwell Time Analysis

Deep learning based traffic analysis is used to increase the efficiency and safety of traffic. It provides analytics to measure changes over time and send alerts.

  1. Vision-based dwell time analytics is very scalable, its possible to monitor a high number of locations in parallel.
  2. The automation of dwell time with vision systems is more consistent and accurate than human inspection.
  3. Shorter dwell time in public transport leads to improved service quality and cost savings due to efficiency improvements.
  4. In logistics, dwell time is an important performance metric. Constant monitoring makes it possible to detect bottlenecks and supply chain issues faster.
  5. Dwell time optimization enables significant cost savings by avoiding detention costs for shippers or increasing the operational efficiency of downstream processes.
Industries
Last updated
February 7, 2022
Usage
Requires Viso Suite
Support

How to get started

This solution is built on Viso Suite, the all-in-one computer vision platform to deploy, run and scale the solution with powerful tools and infrastructure.

To get started, request a personal demo, we will put together a plan that includes all the services you need to get started.

You are in good company

Other Solutions

Ergonomic Risk Analysis
Ergonomic Risk Analysis
AI-based ergonomic risk analysis using cameras to detect the human posture of employees.
Get started
Object counting
Object counting
Use cameras for automated object counting with deep learning models.
Get started
Automatic Number Plate Recognition (ANPR)
Automatic Number Plate Recognition
Automated Number Plate Recognition to identify vehicles in real-time.
Get started
Would you like a demo?

See how your team can build your real-world AI vision systems faster with our end-to-end solution.

A problem was detected in the following Form. Submitting it could result in errors. Please contact the site administrator.

Schedule a live demo

Not interested?

We’re always looking to improve, so please let us know why you are not interested in using Computer Vision with Viso Suite.