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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.
Last updated
February 7, 2022
Requires Viso Suite

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.

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