Guangjie Han

Prof. Dr. Guangjie Han

Department of Information and Communication System, Hohai University, Changzhou 213022, China
+1
orcid

Research Focus & Metrics

Academic Career Length

20Years (2007-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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5 August 2011 in Telecommunication Systems
Verified
Journal Article
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Guangjie HanGuangjie Han
Guangjie Han
HXHuihui Xu
Huihui Xu
Trung Q. DuongTrung Q. Duong
Trung Q. Duong
JJJinfang Jiang
Jinfang Jiang
Takahiro HaraTakahiro Hara
Takahiro Hara

1 September 2020 in IEEE Network
Verified
Journal Article
Closed access
LZLiang Zhao
Liang Zhao
Guangjie HanGuangjie Han
Guangjie Han
ZLZhuhui Li
Zhuhui Li
LSLei Shu
Lei Shu

9 January 2016 in Sensors
Verified
Journal Article
Open access
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RYRuiyun Yu
Ruiyun Yu
YYYu Yang
Yu Yang
LYLeyou Yang
Leyou Yang
Guangjie HanGuangjie Han
Guangjie Han
OMOguti Ann Move
Oguti Ann Move
Air quality information such as the concentration of PM2.5 is of great significance for human health and city management. It affects the way of traveling, urban planning, government policies and so on. However, in major cities there is typically only a limited number of air quality monitoring stations. In the meantime, air quality varies in the urban areas and there can be large differences, even between closely neighboring regions. In this paper, a random forest approach for predicting air quality (RAQ) is proposed for urban sensing systems. The data generated by urban sensing includes meteorology data, road information, real-time traffic status and point of interest (POI) distribution. The random forest algorithm is exploited for data training and prediction. The performance of RAQ is evaluated with real city data. Compared with three other algorithms, this approach achieves better prediction precision. Exciting results are observed from the experiments that the air quality can be inferred with amazingly high accuracy from the data which are obtained from urban sensing.

13 February 2012 in Sensors
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Journal Article
Open access
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Guangjie HanGuangjie Han
Guangjie Han
JJJinfang Jiang
Jinfang Jiang
LSLei Shu
Lei Shu
YXYongjun Xu
Yongjun Xu
FWFeng Wang
Feng Wang
In Underwater Wireless Sensor Networks (UWSNs), localization is one of most important technologies since it plays a critical role in many applications. Motivated by widespread adoption of localization, in this paper, we present a comprehensive survey of localization algorithms. First, we classify localization algorithms into three categories based on sensor nodes’ mobility: stationary localization algorithms, mobile localization algorithms and hybrid localization algorithms. Moreover, we compare the localization algorithms in detail and analyze future research directions of localization algorithms in UWSNs.

12 January 2018 in IEEE Communications Magazine
Verified
Journal Article
Closed access
JJJinfang Jiang
Jinfang Jiang
Guangjie HanGuangjie Han
Guangjie Han
Nowadays, mini-drones, officially called unmanned aerial vehicles, are widely used in many military and civilian fields. Compared to traditional ad hoc networks, the mobile ad hoc networks established by UAVs are more efficient in completing complex tasks in harsh environments. However, due to the unique characteristics of UAVs (e.g., high mobility and sparse deployment), existing protocols or algorithms cannot be directly used for UAVs. In this article, we focus on the routes designed for UAVs, and aim to present a somewhat complete survey of the routing protocols. Moreover, the performance of existing routing protocols is compared in detail, which naturally leads to a great number of open research problems that are outlined afterward.