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Design tools ensure component compatibility, create autonomous driving tests

SAE Truck & Off-Highway Engineering: October 2019

Terry Costlow
  • Magazine Article
  • 19TOFHP10_10
Published 2019-10-01 by SAE International in United States

Simulation has become a critical element in design and validation, expanding its reach to nearly every facet of vehicle development. Partnerships and cloud computing are among the techniques being used as tool developers strive to make it easier for programmers and engineers to see how the many elements in vehicle systems interact.

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SAE Truck & Off-Highway Engineering: August 2019

Terry Costlow
  • Magazine Article
  • 19TOFHP08_02
Published 2019-08-01 by SAE International in United States

Data mining helps users and equipment developers use data from on-vehicle sensors to work more efficiently.

The huge volumes of data created by on-vehicle systems are being mined to bring a range of benefits to vehicle operators and fleet managers. Predictive maintenance is becoming more common, while data mining is helping OEM design and manufacturing teams enhance their programs.

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Automated Object Detection in an Image

  • Magazine Article
  • TBMG-34908
Published 2019-08-01 by Tech Briefs Media Group in United States

Recent developments in machine vision have demonstrated remarkable improvements in the ability of computers to properly identify objects in a viewing field. Most of these advances rely on color-texture analyses that require target objects to possess one or more highly distinctive, local features that can be used as distinguishing characteristics for a classification algorithm. Many objects, however, consist of materials that are widely prevalent across a variety of object categories. For example, many trees have leaves, many manmade objects are made of painted metal, and so forth, such that color-texture detectors configured/trained to identify leaves or painted metal are good for some categorizations, but not for others. Much less effort has been made to characterize objects based on shape, or the particular way the component features are arranged relative to one another in two-dimensional (2D) image space.

Cable Construction for Machine Vision Connectivity

  • Magazine Article
  • TBMG-34882
Published 2019-08-01 by Tech Briefs Media Group in United States

Along with the onslaught of Internet of Things (IoT) and wirelessly enabled devices, cloud connectivity has become a major benefit for a range of applications from commercial to military. As of 2018, Ethernet networking surpassed Fieldbus technology in industrial settings (Figure 1). This is partly due to the growth of industrial IoT (IIoT) where the central gateway to all the sensor nodes is necessarily connected to the cloud via a hardwired Ethernet connection. In industrial settings, power over Ethernet (PoE) links can serve cameras for machine vision, to sensors for multi-modal processing capabilities. This article overviews industrial Ethernet, some of its major pain points including networking dynamics, and cable construction specific to industrial applications.

Why Cloud QMS Better Supports Regulatory Compliance

  • Magazine Article
  • TBMG-34806
Published 2019-07-01 by Tech Briefs Media Group in United States

Companies regulated by the U.S. Food and Drug administration (FDA) need to establish current good manufacturing practices (CGMPs) as part of Title 21 CFR part 820 requirements. This includes creation of quality systems to ensure development of safe and effective devices. More specifically, medical device manufacturers must establish methods and procedures to design, produce, and deliver devices that meet the quality system standard.1

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Complexity of Autonomous-Systems Simulation, Validation Soars to the Clouds

Autonomous Vehicle Engineering: July 2019

Terry Costlow
  • Magazine Article
  • 19AVEP07_03
Published 2019-07-01 by SAE International in United States

Scalable, cloud-based architectures are gaining greater acceptance for simulating and testing the myriad development aspects of automated driving.

As the auto industry strives to improve safety and edge towards high-level automated driving, the complexity of proving that electronic vehicle controls will perform safely is skyrocketing. Simulation's expanding role in systems validation is prompting many tool providers to move to scalable, cloud-based architectures that run operations in parallel to shorten analysis times.

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Efficient Security for Cloud-Based Machine Learning

  • Magazine Article
  • TBMG-33922
Published 2019-03-01 by Tech Briefs Media Group in United States

Outsourcing machine learning is a rising trend in industry. Major tech firms have launched cloud platforms that conduct computation-heavy tasks, such as running data through a convolutional neural network (CNN) for image classification. Resource-strapped small businesses and other users can upload data to those services for a fee and get back results in several hours.

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Methodology to Recognize Vehicle Loading Condition - An Indirect Method Using Telematics and Machine Learning

Mahindra Research Valley-Vaisakh Venugopal, Paul Raj Bob, Vipin Nair
Published 2019-01-09 by SAE International in United States
Connected vehicles technology is experiencing a boom across the globe. Vehicle manufacturers have started using telematics devices which leverage mobile connectivity to pool the data. Though the primary purpose of the telematics devices is location tracking, the additional vehicle information gathered through the devices can bring in much more insights about the vehicles and its working condition. Cloud computing is one of the major enabled for connected vehicles and its data-driven solutions. On the other hand, machine learning and data analytics enable a rich customer experience understanding different inferences from the available data. From a fleet owner perspective, the revenue and the maintenance costs are directly related to the usage conditions of the vehicle. Usage information like load condition could help in efficient vehicle planning, drive mode selection and proactive maintenance [1]. A common approach to vehicle load condition detection is by using exclusive load sensing sensors. This paper explores a possibility of detecting vehicle load conditions without making use of any sensors. Instead, a supervised machine learning model is developed to recognize real-time loading…
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Smart Actuators Deliver on the Promise of Industry 4.0

  • Magazine Article
  • TBMG-33357
Published 2018-12-01 by Tech Briefs Media Group in United States

As Industry 4.0 initiatives bring more and more industrial axes of motion into the realm of automation, the need for cost-effective control across them grows as well. Advances in robotics, connectivity, cloud computing, artificial intelligence, data analysis, mobility, and numerous other areas are converging to push global industry to new plateaus of operational efficiency and creating roles for automated actuators in places previously thought impractical.

Smart Sensor Technology for the IoT

  • Magazine Article
  • TBMG-33212
Published 2018-11-01 by Tech Briefs Media Group in United States

Internet of Things (IoT) applications — whether for city infrastructures, factories, or wearable devices — use large arrays of sensors collecting data for transmission over the Internet to a central, cloud-based computing resource. Analytics software running on the cloud computers reduces the huge volumes of generated data into actionable information for users, and commands to actuators back out in the field.