H. Bryan Riley

H. Bryan Riley
Clemson University | CU · Department of Mechanical Engineering

Doctor of Philosophy (Ph.D.)

About

14
Publications
5,868
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
248
Citations
Citations since 2016
8 Research Items
223 Citations
201620172018201920202021202201020304050
201620172018201920202021202201020304050
201620172018201920202021202201020304050
201620172018201920202021202201020304050
Introduction
H. Bryan Riley, Ph.D., joined the Department of Mechanical Engineering as a Professor of Practice at Clemson University. He will be teaching courses, conducting smart applied manufacturing research, and working in a leadership roll to launch the Clemson University Center for Advanced Manufacturing (CU CAM). A primary focus of CU CAM shall be to provide students with real-world, project centered, and interdisciplinary experiences in advanced manufacturing areas. These and other educational pedagogy will prepare students to be highly recruited for global industry positions as well as successfully complete graduate degree programs.
Additional affiliations
August 2010 - May 2017
Ohio University
Position
  • Professor (Associate)
Description
  • Teaching, Developnment of EE Undergraduate and Graduate Courses, On-Line EE Master Degree Instructor, Autonomous Vehicle & Situational Awareness
June 2007 - March 2018
Provectus Technical Solutions, LLC
Position
  • Managing Director

Publications

Publications (14)
Article
Full-text available
Advanced sensing technologies are providing for greater capabilities to discern and classify details of objects as they appear in actual environments as experienced by nonprofessional drivers. Distinctive geometric configurations of new sensory devices including but not limited to infrared (abbreviated as IR) and LIDAR sensory units are appearing a...
Conference Paper
Full-text available
Sensing techniques using varied configurations of infrared (IR) devices are rapidly becoming a proven approach for autonomous vehicles. In this paper, we present an investigation and corresponding results of embedding these sensors in a prototype robotic model and examine its performance. The results support IR sensing as a viable alternative to a...
Conference Paper
Rapid prototyping and additive manufacturing through 3D printing has significantly impacted business, industrial, and research activities as a rapidly emerging technology whose significance continues to grow. This new technology has been shown to lower the manufacturing costs in a plethora of fields that range in diversity from manufacturing nuclea...
Article
Full-text available
Recent advancements in 3D printing, sometimes referred to as additive manufacturing is considered a game changer relative to rapid prototyping. The industrial, military, commercial, aerospace as well as the automotive industry have made significant gains due to this technology. The 3D printing market is expected to reach $8.43 billion by 2020, at a...
Poster
Full-text available
This project presents a small scale design must first be implemented to ensure proof of concept and give the team a broad understanding in fundamentals of autonomous design.
Article
Full-text available
Diabetic retinopathy may potentially lead to blindness without early detection and treatment. In this research, an approach to automate the identification of the presence of diabetic retinopathy from color fundus images of the retina has been proposed. Classification of an input fundus image into one of the three classes, healthy/normal, Non-Prolif...
Article
Full-text available
ECG is an important tool to measure health and disease detection. Due to many noise sources, this signal has to be denoised and presented in a clear waveform. Noise sources may consist of power line interference, external electromagnetic fields, random body movements or respiration. In this project, five common and important denoising methods are p...
Article
Full-text available
This research aims to develop a driver drowsiness monitoring system by analyzing the electroencephalographic (EEG) signals in a software scripted environment and using a driving simulator. These signals are captured by a multi-channel electrode system. Any muscle movement impacts the EEG signal recording which translates to artifacts. Therefore, no...
Conference Paper
This paper presents a wireless channel characterization for a short-range, temperate, medium density forest environment. This environment and frequency band have not been thoroughly characterized. We conducted measurements at a center frequency of 5.12 GHz with a 50MHz bandwidth signal and obtained impulse response estimates. Measured results for d...
Conference Paper
Full-text available
The desire for increased comfort in both ride and quietness of passenger vehicles is receiving increased attention. To address this concern we develop an active system for vibration control that reduces vibrations on the body and simultaneously reduces noise inside the passenger cabin. The algorithm development is based upon well known principles f...

Questions

Question (1)
Question
Commercial, industrial, and military vehicles are required to safely navigate predetermine paths in degraded visual environments (i.e., fog, snow, heavy rain, dust, ect.). Various techniques based on sensor fusion (i.e., CCD cameras, RADAR, Laser sensors, ultrasonic sensors, ect.), Machine Learning/AI, human-aided operations and other are applied.

Network

Cited By

Projects

Projects (2)
Project
Determine feasibility and robustness of low-cost sensors for real-world autonomous vehicle following functions.