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: | Siegel, Joshua Eric, Sun, Yongbin, Sarma, Sanjay E |
---|---|
Other Authors: | Massachusetts Institute of Technology. Department of Mechanical Engineering |
Format: | Book |
Language: | en_US |
Published: |
Springer International Publishing
2020
|
Online Access: | https://hdl.handle.net/1721.1/124000 |
Similar Items
-
Vehicular engine oil service life characterization using On-Board Diagnostic (OBD) sensor data
by: Siegel, Joshua E, et al.
Published: (2018) -
Real-time Deep Neural Networks for internet-enabled arc-fault detection
by: Siegel, Joshua E, et al.
Published: (2019) -
PointGrow: Autoregressively Learned Point Cloud Generation with Self-Attention
by: Sun, Yongbin, et al.
Published: (2021) -
Using Open Channels to Trigger the Invited, Unintended Consequences of the Internet of Things
by: Siegel, Joshua Eric, et al.
Published: (2020) -
A Review on Automotive Tires Significant Characteristic Identification for General Consumers
by: Ahmad Noor Syukri, Zainal Abidin, et al.
Published: (2022)