Ubiquitous Machine Vision

Ubiquitous Machine Vision with Adaptive Wireless Networking and Edge Computing
Electrical and Computer Engineering

ECE researchers Dr. Tao Han and Dr. Chen Chen received funding from the NSF to realize ubiquitous machine vision (UbiVision) and enable efficient utilization of networked cameras for information extraction and sharing. To research this goal, the PIs are using techniques and perspectives from wireless networking, computer vision, and edge computing to solve fundamental research problems in the ubiquitous camera system. This interdisciplinary research project aims to develop a platform to enable people from all over the world to share their smart cameras, which can be Uber, Airbnb, or Mobike in the context of smart cameras. For example, a person in New York City can “see” what is happening in Los Angeles via a wearable camera shared by another person located in Los Angeles. UbiVision is designed with novel network protocols and machine learning algorithms to dynamically manage highly coupled resources and functions across multiple technology domains: 1) camera functions such as image preprocessing and embedded machine vision; 2) network resources in the radio access network; 3) computation resources and machine vision on the edge servers. Drs. Han and Chen were awarded a $403,800 grant from NSF’s Computer and Information Science and Engineering (CISE) to support this research. This project fosters interdisciplinary research, provides a unique training program to undergraduate and graduate students, and has a high potential to introduce transformative technologies that enable new real-life products and services.