Enabling Interactive Perception Applications on Edge Devices

在边缘设备上启用交互式感知应用

• 批准号: RGPIN-2019-05989
• 负责人: Zheng, Rong
• 金额: $ 4.01万
• 依托单位: McMaster University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=713454
• 关键词: Enabling; Interactive; Perception; Applications; Edge

Perception means awareness of the elements of environment through physical sensation. With increasing processing, communication and sensing capabilities of mobile and embedded devices, interactive perception applications are gaining popularity. These applications use cameras and other high-rate sensors to perform perception tasks, such as speech or object recognition, enable natural human-machine interfaces and interactive augmented-reality experiences, and provide inputs to in-situ decision making such as controlling an autonomous vehicle. Interactive perception applications require real-time processing of streaming data from sensors to provide timely response. Due to limited compute and storage resources on edge devices, traditionally, part or all of the compute-intensive components of such applications are offloaded to the cloud. However, such approaches not only introduce non-negligible extra latency from network communication -- in some cases, rendering the application unresponsive, but also pose privacy concerns by uploading to and storing user data on remote servers. The long-term goal of my research program is to co-design computation models with networked embedded and mobile systems. The short-term goal is to enable interactive perception applications on edge devices by overcoming their resource barriers. To realize the short- term goal, we plan to pursue four main research activities in the five-year period, namely, i) benchmarking performance bottleneck and power efficiency of interactive applications on edge devices, ii) developing distributed models for cooperating edge devices, iii) designing model caching algorithms, and iv) run- time configuration optimization. A total of seven HQP (2 PhDs, 1 Master's and 5 undergraduate research students) will be trained through the duration of the program. The research is at the intersection of mobile computing, networking and machine learning. It will result in a better understanding of the interplay between systems considerations and machine learning models for interactive perception applications. The proposed research program will offer HQP great training opportunities in skillsets highly valued in both academia and industry.

感知是指通过身体感觉对环境要素的意识。随着移动和嵌入式设备的处理、通信和传感能力的提高，交互式感知应用越来越受欢迎。这些应用程序使用摄像头和其他高速传感器来执行感知任务，如语音或物体识别，实现自然人机界面和交互式增强现实体验，并为控制自动驾驶汽车等现场决策提供输入。交互式感知应用需要实时处理来自传感器的流数据，以提供及时的响应。