Automotive Diagnostics as a Service: An Artificially Intelligent Mobile Application for Tire Condition Assessment
Vehicle tires must be maintained to assure performance, efficiency, and safety. Though vehicle owners may monitor tread depth and air pressure, most are unaware of the safety risks of degrading rubber. This paper identifies the need for tire material condition monitoring and develops a densely conne...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Book |
| Language: | en_US |
| Published: |
Springer International Publishing
2020
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| Online Access: | https://hdl.handle.net/1721.1/124000 |
| _version_ | 1826213941122957312 |
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| author | Siegel, Joshua Eric Sun, Yongbin Sarma, Sanjay E |
| author2 | Massachusetts Institute of Technology. Department of Mechanical Engineering |
| author_facet | Massachusetts Institute of Technology. Department of Mechanical Engineering Siegel, Joshua Eric Sun, Yongbin Sarma, Sanjay E |
| author_sort | Siegel, Joshua Eric |
| collection | MIT |
| description | Vehicle tires must be maintained to assure performance, efficiency, and safety. Though vehicle owners may monitor tread depth and air pressure, most are unaware of the safety risks of degrading rubber. This paper identifies the need for tire material condition monitoring and develops a densely connected convolutional neural network to identify cracking from smartphone photographs. This model attains an accuracy of 81.2% on cropped outsample images, besting inexperienced humans’ 55% performance. We develop a web service using this model as the basis of an AI-backed “Diagnostics-as-a-Service” platform for online vehicle condition assessment. By encoding knowledge of visual risk indicators into a neural network model operable from a user’s trusted smartphone, we raise awareness of the risk of degraded rubber and improve vehicle safety without requiring specialized operator training. |
| first_indexed | 2024-09-23T15:57:16Z |
| format | Book |
| id | mit-1721.1/124000 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T15:57:16Z |
| publishDate | 2020 |
| publisher | Springer International Publishing |
| record_format | dspace |
| spelling | mit-1721.1/1240002022-09-29T17:17:55Z Automotive Diagnostics as a Service: An Artificially Intelligent Mobile Application for Tire Condition Assessment Siegel, Joshua Eric Sun, Yongbin Sarma, Sanjay E Massachusetts Institute of Technology. Department of Mechanical Engineering Subirana, Brian Vehicle tires must be maintained to assure performance, efficiency, and safety. Though vehicle owners may monitor tread depth and air pressure, most are unaware of the safety risks of degrading rubber. This paper identifies the need for tire material condition monitoring and develops a densely connected convolutional neural network to identify cracking from smartphone photographs. This model attains an accuracy of 81.2% on cropped outsample images, besting inexperienced humans’ 55% performance. We develop a web service using this model as the basis of an AI-backed “Diagnostics-as-a-Service” platform for online vehicle condition assessment. By encoding knowledge of visual risk indicators into a neural network model operable from a user’s trusted smartphone, we raise awareness of the risk of degraded rubber and improve vehicle safety without requiring specialized operator training. 2020-03-03T21:23:30Z 2020-03-03T21:23:30Z 2018-06 Book http://purl.org/eprint/type/JournalArticle 9783319943602 9783319943619 0302-9743 1611-3349 https://hdl.handle.net/1721.1/124000 Siegel, Joshua E. et al. "Automotive Diagnostics as a Service: An Artificially Intelligent Mobile Application for Tire Condition Assessment." International Conference on AI and Mobile Services, June 2018, Seattle, WA, USA, Springer, June 2018 © 2018 Springer en_US http://dx.doi.org/10.1007/978-3-319-94361-9_13 International Conference on AI and Mobile Services http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Springer International Publishing Subirana, Brian |
| spellingShingle | Siegel, Joshua Eric Sun, Yongbin Sarma, Sanjay E Automotive Diagnostics as a Service: An Artificially Intelligent Mobile Application for Tire Condition Assessment |
| title | Automotive Diagnostics as a Service: An Artificially Intelligent Mobile Application for Tire Condition Assessment |
| title_full | Automotive Diagnostics as a Service: An Artificially Intelligent Mobile Application for Tire Condition Assessment |
| title_fullStr | Automotive Diagnostics as a Service: An Artificially Intelligent Mobile Application for Tire Condition Assessment |
| title_full_unstemmed | Automotive Diagnostics as a Service: An Artificially Intelligent Mobile Application for Tire Condition Assessment |
| title_short | Automotive Diagnostics as a Service: An Artificially Intelligent Mobile Application for Tire Condition Assessment |
| title_sort | automotive diagnostics as a service an artificially intelligent mobile application for tire condition assessment |
| url | https://hdl.handle.net/1721.1/124000 |
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