Dynamic, Data-Driven Design Methodologies for IoT-Based Computer Vision Systems
Abstract
Embedded computer vision (ECV), where analysis of visual information is embedded into application-specific devices and systems, is a promising area for a broad variety of Internet of Things (IoT) applications that are of tremendous societal benefit. Specific application domains that can derive significant benefit from advances in IoT-driven ECV include healthcare, elderly hospice, environmental monitoring, public safety, and surveillance. Additionally, optimized design and integration of IoT and ECV technologies is important in advancing strategic areas of image and video analysis technology, including video summarization, human activity understanding, and semantic summarization, which have been identified as problem areas in which long term investments are needed [8]. The intersection of IoT with that of ECV corresponds to the DDDAS principles of system model updates to more accurately predict system conditions.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Apr 09, 2018
- Source ID
- FA95501810068
Entities
People
- Shuvra Bhattacharyya
Organizations
- Air Force Office of Scientific Research
- United States Air Force
- University of Maryland