sensors-logo

Journal Browser

Journal Browser

Design, System, and Performance of Sensors Networks

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensor Networks".

Deadline for manuscript submissions: closed (31 December 2022) | Viewed by 3092

Special Issue Editor


E-Mail Website
Guest Editor
Artificial Intelligence College, Beijing Technology and Business University, Beijing 10048, China
Interests: multisensor fusion; statistical signal processing; video/image processing; Bayesian theory; time series analysis; artificial intelligence; target tracking and dynamic analysis
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

As the essential component of the Internet of Things and cyber-physical systems, the design of sensor networks and research on information processing methods have significant value. Sensor networks have a wide range of applications, such as industry, agriculture, environmental monitoring, transportation applications, etc. The design of a sensor network involves hardware, sensor nodes, etc. Wireless sensor networks also need to consider the gateway and energy source. Evaluating the performance of sensor networks is also the key to designing and using sensor networks.

With the development of sensor technology, communication technology, automatic control technology, multi-sensor fusion technology, artificial intelligence, etc., sensor network research has reached a new stage of development that includes new theories, methods, and technologies.

This Special Issue aims to report on innovative ideas and solutions for the design, system, and performance of sensors networks in the emerging applications and methods era while focusing on development, adoption, and applications.

Prof. Dr. Xue-Bo Jin
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Internet of Things
  • industrial networks
  • wireless sensor networks
  • zigbee network
  • camera sensor networks
  • localization algorithms
  • network structure
  • underwater wireless sensor networks
  • cognitive wireless sensor networks

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Research

19 pages, 12538 KiB  
Article
A Two-Stage Feature Point Detection and Marking Approach Based on the Labeled Multi-Bernoulli Filter
by Jiahui Yang and Weifeng Liu
Sensors 2022, 22(14), 5083; https://doi.org/10.3390/s22145083 - 06 Jul 2022
Viewed by 1136
Abstract
In recent years, various algorithms using random finite sets (RFS) to solve the issue of simultaneous localization and mapping (SLAM) have been proposed. Compared with the traditional method, the advantage of the RFS method is that it can avoid data association, landmark appearance [...] Read more.
In recent years, various algorithms using random finite sets (RFS) to solve the issue of simultaneous localization and mapping (SLAM) have been proposed. Compared with the traditional method, the advantage of the RFS method is that it can avoid data association, landmark appearance and disappearance, missed detections, and false alarms in Bayesian recursion. There are many problems in the existing robot SLAM methods, such as low estimation accuracy, poor back-end optimization, etc. On the basis of previous studies, this paper presents a labeled random finite set (L-RFS) SLAM method. We describe a scene where the sensor moves along a given path and avoids obstacles based on the L-RFS framework. Then, we use the labeled multi-Bernoulli filter (LMB) to estimate the state of the sensor and feature points. At the same time, the B-spline curve is used to smooth the obstacle avoidance path of the sensor. The effectiveness of the algorithm is verified in the final simulation. Full article
(This article belongs to the Special Issue Design, System, and Performance of Sensors Networks)
Show Figures

Figure 1

Back to TopTop