AN IP-BASED LIVE DATABASE APPROACH TO SURVEILLANCE APPLICATION DEVELOPMENT

With the proliferation of inexpensive cameras, video surveillance applications are becoming ubiquitous in many domains such as public safety and security, manufacturing, intelligent transportation systems, and healthcare. IP-based video surveillance technologies, in particular, are able to bring traditional video surveillance centers to virtually any computer at any location with an Internet connection. Today’s IP-based video surveillance systems, however, are designed for specific classes of applications. For instance, one cannot use a system designed for incident detection on highways to monitor patients in a healthcare facility. To support rapid development of video surveillance applications, we designed and implemented a new class of general purpose database management system, the live video database management system (LVDBMS). We view networked IP cameras as a special class of storage devices, and allow the user to formulate ad hoc queries expressed over live video feeds. These continuous queries are processed in real time using novel distributed computing techniques. With this environment, the users are able to develop various specific web-based video surveillance systems for a variety of applications. These systems can coexist in a unified LVDBMS framework to share the expensive deployment and operating costs of the camera networks. Our contribution is the introduction of a live database approach to video surveillance software development. In this paper, we describe our prototype and present the live video data model, the query language, and the query processing technique. 1

A survey to determine the adequacy of information the geriatric diabetic patient has about his disease.

I he diabetic patient is faced with a disease that does not significantly affect his appearance or his sense of well-being after control is achieved. However, this condition will persist for the rest of his life and will require considerable attention to time-consuming details. These characteristics may cause those who give care or assist in the care of the diabetic patient to assume a casual attitude toward the management of a chronic disease in which the constant control largely depends on the quality of sustained professional car

Scene Understanding For Real Time Processing Of Queries Over Big Data Streaming Video

With heightened security concerns across the globe and the increasing need to monitor, preserve and protect infrastructure and public spaces to ensure proper operation, quality assurance and safety, numerous video cameras have been deployed. Accordingly, they also need to be monitored effectively and efficiently. However, relying on human operators to constantly monitor all the video streams is not scalable or cost effective. Humans can become subjective, fatigued, even exhibit bias and it is difficult to maintain high levels of vigilance when capturing, searching and recognizing events that occur infrequently or in isolation. These limitations are addressed in the Live Video Database Management System (LVDBMS), a framework for managing and processing live motion imagery data. It enables rapid development of video surveillance software much like traditional database applications are developed today. Such developed video stream processing applications and ad hoc queries are able to reuse advanced image processing techniques that have been developed. This results in lower software development and maintenance costs. Furthermore, the LVDBMS can be intensively tested to ensure consistent quality across all associated video database applications. Its intrinsic privacy framework facilitates a formalized approach to the specification and enforcement of verifiable privacy policies. This is an important step towards enabling a general privacy certification for video surveillance systems by leveraging a standardized privacy specification language. With the potential to impact many important fields ranging from security and assembly line monitoring to wildlife studies and the environment, the broader impact of this work is clear. The privacy framework protects the general public from abusive use of surveillance technology; iii success in addressing the trust issue will enable many new surveillance-related applications. Although this research focuses on video surveillance, the proposed framework has the potential to support many video-based analytical applications

KEYNOTE ADDRESS - From Student to Educator: The Evolution of Diversity and Inclusion

During this interactive presentation, Dr. Lucero will share her experiences as a woman of color with hearing loss and a deaf educator; through her storytelling, the audience will reflect on how evolving perspectives on diversity and inclusion have informed current practices in deaf education

From Student to Educator: Reflecting on the Evolution of Diversity and Inclusion in Deaf Education

What is now considered best practices for working with culturally and linguistically diverse families and in inclusive education in deaf education has changed drastically from what was in place in 1979 when Renee Lucero was diagnosed with a hearing loss. During this interactive presentation, we will reflect on how evolving perspectives on diversity and inclusion have informed current practices in deaf education. Dr. Lucero will share her personal and professional experiences as a woman of color with hearing loss and a deaf educator to demonstrate how much the landscape of deaf education has changed in recent decades. As a result of this activity, participants will be able to: Summarize evidence-informed practices when serving culturally and linguistically diverse families Identify at least three new evidence-informed practices to directly implement into their own teaching Describe the evolution of best practices in diversity and inclusive education in deaf educatio