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The brain processes sensory information rapidly due to parallel processing, which involves sending data across multiple neural pathways at the same time. This method allows the brain to manage various sensory qualities, such as shapes, colors, movements, and locations, all concurrently. For instance, when observing a forest landscape, the brain simultaneously processes the movement of leaves, the shapes of trees, the depth between them, and the various shades of green. This enables a quick and...
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Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...
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Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. Consider a lifting tong carrying a 100 kg load. It comprises movable sections DAF and CBG linked together with member AB.
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A toggle clamp is a mechanical device commonly used for holding and clamping objects in various applications, such as woodworking, metalworking, and assembly operations. Consider a toggle clamp subjected to a force of 200 N at the handle. The vertical clamping force can be calculated, provided the dimensions of the toggle clamp are known.
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Distribution reliability in electrical power systems is critical for ensuring an uninterrupted power supply to consumers at minimal cost. According to IEEE Standard Terms, reliability is the probability that a device will function without failure over a specified time period or amount of usage. For electric power distribution, this translates to maintaining continuous power supply and addressing customer concerns over power outages. Several indices, as defined by IEEE Standard 1366-2012, are...
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Transformers in distribution systems can be broadly categorized into distribution substation transformers and other distribution transformers. They are crucial for stepping down high transmission voltages to levels suitable for distribution and end-user applications.
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Related Experiment Video

Updated: Oct 30, 2025

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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Deploying a smart queuing system on edge with Intel OpenVINO toolkit.

Rishit Dagli1, Süleyman Eken2

  • 1Thakur International School Mumbai, Mumbai, India.

Soft Computing
|July 5, 2021
PubMed
Summary
This summary is machine-generated.

Edge computing enables smart queuing systems (SQS) on low-cost devices. This AI solution leverages existing hardware, making advanced queue management accessible and cost-effective across various sectors.

Keywords:
Edge AIEdge computingIntel OpenVINOOptimizationSmart queuing systemSoft computing

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Area of Science:

  • Computer Vision
  • Edge AI
  • Machine Learning

Background:

  • Advancements in computational power and specialized hardware enable edge machine learning, particularly inference.
  • OpenVINO toolkit accelerates the development and deployment of deep learning computer vision applications across diverse hardware.

Purpose of the Study:

  • To develop an accessible smart queuing system (SQS) for edge deployments.
  • To enable SQS deployment on low-cost, pre-existing hardware, reducing deployment costs.

Main Methods:

  • Developed a smart queuing system (SQS) utilizing deep learning algorithms for edge deployment.
  • Validated the SQS performance across multiple edge devices: CPU, integrated GPU (iGPU), vision processing unit (VPU), and field-programmable gate arrays (FPGAs).

Main Results:

  • Demonstrated the feasibility of creating a video AI solution for smart queuing on the edge.
  • Experimental results confirm the promising performance of edge-deployed SQS.

Conclusions:

  • Edge AI solutions like SQS can be effectively deployed on affordable, existing hardware.
  • This approach significantly reduces the cost and increases the accessibility of intelligent queue management systems.