Light Deep Learning based Edge Safety Surveillance

Lou, Yimo and Cao, Wengang and He, Zhimin and Gui, Guan (2020) Light Deep Learning based Edge Safety Surveillance. In: Mobimedia 2020, 27-28 August 2020, Cyberspace.

[thumbnail of eai.27-8-2020.2295046.pdf]
eai.27-8-2020.2295046.pdf - Published Version

Download (1MB) | Preview


Safety is considered as the first important factor in many industries such as construction sites. Hence, artificial intelligence based safety surveillance techniques have been received strong attentions in recent years. Conventional surveillance systems for monitoring whether the workers wearing helmets are not easy to install and carry, and the largest trouble is that the system needs considerable computation, which is not that simple to satisfy the requirement of hardware. Considering the characteristic about construction sites, in this paper, we proposed a new system based on CenterNet with MobileNet-V2 as backbone. It has a video camera, a marginal device embedded with Jetson TX2 and wireless communication routers to ensure real-time transmission about live-scene about construction sites. After inspection, the light-weight network we proposed can be run in portable marginal device smoothly and stably with slight loss of average precision.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: intelligence safety surveillance centernet mobilenet-v2 marginal devices
Subjects: Q Science > QA Mathematics > QA76 Computer software
Depositing User: EAI Editor I.
Date Deposited: 04 Feb 2021 14:23
Last Modified: 04 Feb 2021 14:23

Actions (login required)

View Item
View Item