Construction of building fire information monitoring model based on adaptive clustering scheduling Online publication date: Mon, 05-Aug-2019
by Ying Li; Lian Xue
International Journal of Internet Protocol Technology (IJIPT), Vol. 12, No. 3, 2019
Abstract: In order to solve the problem of unsatisfactory monitoring information transmission and large time overhead during conventional building fire monitoring, an optimisation method of building fire information monitoring based on adaptive clustering scheduling is proposed. In this method, a channel model for building fire information monitoring is constructed through the bi-directional link transmission control method, and then node deployment for building fire information monitoring is optimised through the shortest path optimisation method. The deployment of the largest coverage of fire information monitoring sensor nodes is designed through the self-adaptive rotation scheduling, and balance control of the output link layer of internet of things is performed through the adaptive clustering scheduling method to improve the accurate forwarding and real-time transmission capabilities of internet of things for fire detection information, and then a building fire information monitoring model is constructed. Experimental results show that the proposed method can effectively improve the success rate of fire information monitoring packet forwarding with an average increase of 24.7%, which greatly improves the monitoring information transmission efficiency, and it reduces the time overhead of fire information monitoring by 160s. The proposed method meets the actual needs and ensures the effectiveness of fire monitoring.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Internet Protocol Technology (IJIPT):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com