scholarly journals Device Free Localisation Techniques in Indoor Environments

2019 ◽  
Vol 69 (4) ◽  
pp. 378-388 ◽  
Author(s):  
K S Anusha ◽  
Ramachandran Ramanathan ◽  
M Jayakumar
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Location Estimation ◽  
Wireless Sensor ◽  
Ultrasonic Frequency ◽  
Indoor Environments ◽  
Research Directions ◽  
Positioning Systems ◽  
Potential Benefits ◽  
Device Free

The location estimation of a target for a long period was performed only by device based localisation technique which is difficult in applications where target especially human is non-cooperative. A target was detected by equipping a device using global positioning systems, radio frequency systems, ultrasonic frequency systems, etc. Device free localisation (DFL) is an upcoming technology in automated localisation in which target need not equip any device for identifying its position by the user. For achieving this objective, the wireless sensor network is a better choice due to its growing popularity. This paper describes the possible categorisation of recently developed DFL techniques using wireless sensor network. The scope of each category of techniques is analysed by comparing their potential benefits and drawbacks. Finally, future scope and research directions in this field are also summarised.

scholarly journals A Research Cluster based Scheme for Node Positioning in Indoor Environment

2019 ◽  
Vol 8 (6S) ◽  
pp. 79-83
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Indoor Environment ◽  
Cluster Head ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Location Estimation ◽  
Wireless Sensor ◽  
Localization Error ◽  
Network Efficiency

Location estimation in Wireless Sensor Network (WSN) is mandatory to achieve high network efficiency. Identifying the positions of sensors is an uphill task as monitoring nodes are involved in estimation and localization. Clustered Positioning for Indoor Environment (CPIE) is proposed for estimating the position of the sensors using a Cluster Head (CH) based mechanism. The CH estimates the number of neighbor nodes in each floor of the indoor environment. It sends the requests to the cluster members and the positions are estimated based on the Received Signal Strength Indicators (RSSIs) from the members of the cluster. The performance of the proposed scheme is analyzed for both stable and mobile conditions by varying the number of floors. Experimental results show that the propounded scheme offers better network efficiency and reduces delay and localization error

A study on wireless sensor network based indoor positioning systems for context-aware applications

2010 ◽  
Vol 12 (1) ◽  
pp. 53-70 ◽  
Author(s):  
Jing Wang ◽  
R. Venkatesha Prasad ◽  
Xueli An ◽  
Ignas G. M. M. Niemegeers
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Indoor Positioning ◽  
Wireless Sensor ◽  
Context Aware ◽  
Positioning Systems

A Survey on Coverage Control Technology in Wireless Sensor Network

2013 ◽  
Vol 774-776 ◽  
pp. 1556-1559 ◽  
Author(s):  
Kai Guo Qian ◽  
Li Mui ◽  
Tian Ma Zuo ◽  
Zhi Qiang Xu
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Research Literature ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Coverage Problem ◽  
Research Directions ◽  
And Control ◽  
Monitoring Area

Deployment and coverage, studied how to effectively place and control of sensor nodes and to make WSN covered the monitoring area with the purpose of minimum the energy consumption and prolonging the network life cycle under the premise of guarantee the quality of service (QOS),are the primary problems for construction wireless sensor network. This paper analyzes important factors for resolve the coverage problem such as sensing models and deployment way, followed survey the state-of-the art coverage contro1 techniques and presents an overview and analysis of the solution proposed in recent research literature, Further research directions are pointed out in the end.

scholarly journals Human Detection through RSSI Processing with Packet Dropout in Wireless Sensor Network

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Haijing Wang ◽  
Fangfang Zhang ◽  
Wenli Zhang
Keyword(s):  
Wireless Sensor Network ◽  
Real Time ◽  
Sensor Network ◽  
Detection Method ◽  
Human Detection ◽  
Link Quality ◽  
Wireless Sensor ◽  
Packet Dropout ◽  
Data Packets ◽  
Device Free

This paper presents a device-free human detection method for using Received Signal Strength Indicator (RSSI) measurement of Wireless Sensor Network (WSN) with packet dropout based on ZigBee. Packet loss is observed to be a familiar phenomenon with transmissions of WSNs. The packet reception rate (PRR) based on a large number of data packets cannot reflect the real-time link quality accurately. So this paper firstly raises a real-time RSSI link quality evaluation method based on the exponential smoothing method. Then, a device-free human detection method is proposed. Compared to conventional solutions which utilize a complex set of sensors for detection, the proposed approach achieves the same only by RSSI volatility. The intermittent Karman algorithm is used to filter RSSI fluctuation caused by environment and other factors in data packets loss situation, and online learning is adopted to set algorithm parameters considering environmental changes. The experimental measurements are conducted in laboratory. A high-quality network based on ZigBee is obtained, and then, RSSI can be calculated from the receive sensor modules. Experimental results show the uncertainty of RSSI change at the moment of human through the network area and confirm the validity of the detection method.

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