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AWARE Pulse: An Integrated Portal to the AWARE Platform
Benny Leong,Cory Q. Nguyen,Anthony H. Smith,Eric T. Matson,J. Eric Dietz 제어로봇시스템학회 2011 제어로봇시스템학회 국제학술대회 논문집 Vol.2011 No.10
This paper presents the AWARE Pulse application that serves as a web portal to the AWARE platform that provides a mobile wireless network through the use of autonomous robotic agents. In particular, this paper discusses the overall application architecture including the various components within the application, the different roles of the application as well as the integration of AWARE Pulse into the existing AWARE platform.
Daewon Kwon,Dohun Hyun,Miji Kim,Youlim Ko,Helen A McNally,Anthony H Smith 제어로봇시스템학회 2019 제어로봇시스템학회 국제학술대회 논문집 Vol.2019 No.10
In today’s society, we see a constant struggle with intersections that bring in constant crimes. This has become a problem in our society, especially because this is raising a level of risk for other people within the intersection. This means that bikers, walkers, and other cross-traffic drivers are placed in an unfair position because of the decisions and actions of drivers who choose to illegally cross the intersection at a red light. Therefore, this system was put in place to help prevent this and hold drivers accountable in order to ensure that, despite law enforcement not being in place to monitor the situation, consequences are given to those that did not follow this traffic regulation. This allowed for drivers to become aware of the red light cameras and follow the rules, as well as making it possible to give tickets to the drivers that continued to break the rules. While this is the first approach to further developing tracking systems for this type of illegal activity, the cameras remain basic enough that they do not always capture correct image processing. This indicates a need to advance the technology so to better gather information on vehicles and other objects within a camera view.
Deep Learning-based Bird Sound Recognition System with Data Pre-processing
Taepyo Jung,Hyungjin Jeon,Cheolmin Jeon,Aarion Cook,Alayna Weiss,Minsun Lee,Anthony H. Smith 대한전자공학회 2019 대한전자공학회 학술대회 Vol.2019 No.11
Over the past decade, scarecrows have begun moving from stand-alone scarecrows to scarecrows using Internet of Things (IOT) technology. This study focuses on building a “smart” scarecrow that recognizes and detects birds by bird sounds. We propose a bird sound recognition model based on data pre-processing and Convolutional Neural Network (CNN). The hypothesis has been established that noise elimination through data pre-processing is more effective than not using data pre-processing to recognize bird sounds. The results showed that the overall performance of the bird and non-bird sound classification through the pre-processing system was 79.8%, which was no different from that of a system without data preprocessing. However, the proposed model has a 4.81% improvement in non-bird sound classification performance compared to models without data preprocessing.