KEYWORDS: Control systems, Evolutionary algorithms, Data modeling, Telecommunications, Data communications, Feature extraction, Safety, Image processing, Internet of things, Inspection
The power industry is developing fast and there are many power construction projects. With the growing intelligent degree of power system, the construction of power projects become more complicated. There are more than one thousand workers on the site. How to inspect and guarantee the security in construction remotely is a key subject. This paper introduces the principles and means of remote inspection system of infrastructure construction by using internet of things in power systems. Through the application of this system, violations on the construction site can be discovered in a timely and effective manner, and the planning level of construction can be better improved.
With the increase of power load, power infrastructure construction projects are also increasing year by year, and it is of great significance to strengthen the management of power infrastructure construction projects to ensure the safety and compliance of construction sites. In order to better warn the risks of power infrastructure construction sites, artificial intelligence image recognition and neural network technology can be introduced, and the principles of image recognition and neural network technology and the implementation methods in the early warning system of power infrastructure construction are analyzed in detail. By applying the early warning system for power infrastructure construction, construction risks can be well controlled, and the safety of power construction can be improved.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.