Data acquisition system of Internet of Things based on Kohonen multi-protocol adaptation

Changhua Wang; Xiliang Zhang; Xihao Zhu; Hancheng Yu; Shuangjing Ni

doi:10.1117/12.2652742

21 November 2022 Data acquisition system of Internet of Things based on Kohonen multi-protocol adaptation

Changhua Wang, Xiliang Zhang, Xihao Zhu, Hancheng Yu, Shuangjing Ni

Proceedings Volume 12340, International Conference on Frontiers of Traffic and Transportation Engineering (FTTE 2022); 123400U (2022) https://doi.org/10.1117/12.2652742
Event: International Conference on Frontiers of Traffic and Transportation Engineering (FTTE 2022), 2022, Lanzhou, China

Abstract

With the development of highway information, according to the actual demand of highway electromechanical equipment management, this paper designs a multi-protocol internet of things data acquisition system to realize instant messaging and data sharing of electromechanical equipment. The Kohonen neural network is used to train the adaptive module of the existing input protocol. According to the eigenvalues of the header, the shaping number of the end bytes and the length of a single packet of the protocol, the function of automatically selecting the appropriate protocol is realized. In the later stage, the ability to learn more protocol adaptation independently can be realized by updating the protocol knowledge base on the internet of things platform. The results show that the average processing time of Kohonen network for each protocol data is about 109ms, and the average recognition rate reaches 95.45%. Kohonen network can be applied in traffic engineering field and realize the conversion of various information data of electromechanical equipment with different protocols into unified information data through protocol conversion rules.

Citation Download Citation

Changhua Wang, Xiliang Zhang, Xihao Zhu, Hancheng Yu, and Shuangjing Ni "Data acquisition system of Internet of Things based on Kohonen multi-protocol adaptation", Proc. SPIE 12340, International Conference on Frontiers of Traffic and Transportation Engineering (FTTE 2022), 123400U (21 November 2022); https://doi.org/10.1117/12.2652742

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

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.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available