Automotive Diagnostics as a Service: An Artificially Intelligent Mobile Application for Tire Condition Assessment

Siegel, Joshua E.; Sun, Yongbin

doi:10.1007/978-3-319-94361-9_13

Cited by 21 publications

(17 citation statements)

References 15 publications

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“…The designed tool may be integrated with other game-based simulators [68,69] to help quantify and seek to reduce other negative externalities, such as vehicle emissions, using real-world automotive diagnostic data and solutions [70][71][72]. Real-world fault data may also be captured from mobile devices [73][74][75][76][77][78][79] as a means of informing simulation of fuel-wasting faults such that the transit planning strategies reflect true inefficiencies, while a broader game might even model how waste bin placement might impact pedestrian traffic [80] and efficiently mirror cities digitally and in real time [81]. Even industrial processes [82,83] may be mirrored with the aim of improving resource efficiency and reducing waste.…”

Section: Discussionmentioning

confidence: 99%

Modelling Key Performance Indicators in a Gamified Waste Management Tool

et al. 2021

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Broader understanding of waste management has the potential to bring about broad societal change impacting the climate crisis and public health. We present existing waste management tools and commercially-available games involving waste management, highlighting the strengths and opportunities left unaddressed by these tools in educational contexts and planning use cases. A survey motivates the need for enhanced interactive tools providing clear feedback through quick-visibility performance indicators. After identifying an opportunity to build upon highly-detailed multi-criteria simulation tools, we explore the need for easy-to-read performance metrics that will bring to the field of waste management easily identifiable and measurable key performance indicators (KPIs) that vary alongside factors affecting waste management policies. Such metrics are introduced and detailed as part of a unified waste management model. We then develop a representative gamified educational tool based upon this model to be used by students, decision makers planning real-world policies, and the public. This simulator is built upon the Unity Game Engine and emulates waste management techniques and resulting KPIs within the context of a virtual city.

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Section: Discussionmentioning

confidence: 99%

Modelling Key Performance Indicators in a Gamified Waste Management Tool

et al. 2021

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“…Probable fault size or defect shape may be determined through pixel clustering, reporting the coordinates of sufficiently large faults to secondary human inspectors. Building this system into a mobile service [29] or for embedded hardware [27] could further improve in-the-field utility, allows the classifier's use where conventional NDT imaging solutions are infeasible or where inspection latency and turnaround time is a critical concern.…”

Section: Discussionmentioning

confidence: 99%

Automated non-destructive inspection of Fused Filament Fabrication components using Thermographic Signal Reconstruction

Siegel

Beemer

Shepard

2020

Additive Manufacturing

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Manufacturers struggle to produce low-cost, robust and complex components at manufacturing lot-size one. Additive processes like Fused Filament Fabrication (FFF) inexpensively produce complex geometries, but defects limit viability in critical applications. We present an approach to high-accuracy, high-throughput and low-cost automated non-destructive testing (NDT) for FFF interlayer delamination using Flash Thermography (FT) data processed with Thermographic Signal Reconstruction (TSR) and Artificial Intelligence (AI). A Deep Neural Network (DNN) attains 95.4% per-pixel accuracy when differentiating four delamination thicknesses 5mm subsurface in PolyLactic Acid (PLA) widgets, and 98.6% accuracy in differentiating acceptable from unacceptable condition for the same components. Automated inspection enables time-and costefficient 100% inspection for delamination defects, supporting FFF's use in critical and small-batch applications.

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“…The algorithmic foundations for classification and characterization vary by domain and are well-established in literature [2,3,[6][7][8][9][10]. Importantly, classification and characterization algorithms are transferrable across systems, contexts and domains [38][39][40][41][42][43][44][45][46].…”

Section: System Identificationmentioning

confidence: 99%

Cyberphysical Sequencing for Distributed Asset Management with Broad Traceability

Siegel¹,

Falco²

2021

Preprint

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Cyber-Physical systems (CPS) have complex lifecycles involving multiple stakeholders, and the transparency of both hardware and software components' supply chain is opaque at best. This raises concerns for stakeholders who may not trust that what they receive is what was requested. There is an opportunity to build a cyberphysical titling process offering universal traceability and the ability to differentiate systems based on provenance. Today, RFID tags and barcodes address some of these needs, though they are easily manipulated due to non-linkage with an object or system's intrinsic characteristics. We propose cyberphysical sequencing as a low-cost, light-weight and pervasive means of adding track-and-trace capabilities to any asset that ties a system's physical identity to a unique and invariant digital identifier. CPS sequencing offers benefits similar Digital Twins' for identifying and managing the provenance and identity of an asset throughout its life with far fewer computational and other resources. KeywordsDistributed Computing • Computerized instrumentation • Internet of Things • Supply chain management • Security and Privacy • Manufacturing 1 Why Pervasive Digital Traceability (PDT)?Across domains, manufactured and assembled system complexity is increasing. Constituent components require compliance with stringent specifications, must have low defect rates, and increasingly require known provenance relating to origin and interaction histories. At the same time, economic and other constraints affecting production and assembly may necessitate involving diverse and untrusted vendors: a vehicle's parts may be made abroad and assembled domestically, while a medication might be compounded in one country before being shipped to another for packaging and a third for distribution. Power generation plant components might be manufactured globally but require certification in the country of use, while electronics manufacturing for a globally-distributed device may require trust-related integrated circuits to be provided and validated by a single-source vendor.Diverse and distributed supply chains invite substantial risk of counterfeit, compromise, or non-compliance. Providing insight into component origin, provisioning and life before assembly has the potential to make resulting systems more robust, resilient, and broadly usable than is feasible today. Consistent validation of the trusted identity and integrity of a system is necessary to support system tracking, supervision, management, and transferrability to mitigate this risk, particularly for critical applications.Asset supervision may be simple: high assurance systems like space vehicles have robust, metadata-abundant supply chains. In other cases, system, sub-assembly, and component mapping is more difficult. Assembled automobiles, for example, belong to a global registry for Vehicle Identification Numbers that supports asset supervision and management

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Automotive Diagnostics as a Service: An Artificially Intelligent Mobile Application for Tire Condition Assessment

Cited by 21 publications

References 15 publications

Modelling Key Performance Indicators in a Gamified Waste Management Tool

Modelling Key Performance Indicators in a Gamified Waste Management Tool

Automated non-destructive inspection of Fused Filament Fabrication components using Thermographic Signal Reconstruction

Cyberphysical Sequencing for Distributed Asset Management with Broad Traceability

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