Sensor Networks for Underwater Ecosystem Monitoring and Port Surveillance Systems

2014 ◽  
pp. 431-468
Author(s):  
Ali Mansour ◽  
Isabelle Leblond ◽  
Denis Hamad ◽  
Luis Artigas
Keyword(s):  
Sensor Networks ◽  
Surveillance Systems ◽  
Ecosystem Monitoring

Sensor Networks for Underwater Ecosystem Monitoring and Port Surveillance Systems

2017 ◽  
pp. 431-467
Author(s):  
Ali Mansour ◽  
Isabelle Leblond ◽  
Denis Hamad ◽  
Luis Felipe Artigas
Keyword(s):  
Sensor Networks ◽  
Surveillance Systems ◽  
Ecosystem Monitoring

scholarly journals An Environmentally Aware Scheme of Wireless Sensor Networks for Forest Fire Monitoring and Detection

2018 ◽  
Vol 10 (10) ◽  
pp. 102 ◽  
Author(s):  
Yi-Han Xu ◽  
Qiu-Ya Sun ◽  
Yu-Tong Xiao
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Forest Fire ◽  
Forest Fires ◽  
Network Architecture ◽  
Resource Constraints ◽  
Wireless Sensor ◽  
Surveillance Systems ◽  
Fire Monitoring

Forest fires are a fatal threat to environmental degradation. Wireless sensor networks (WSNs) are regarded as a promising candidate for forest fire monitoring and detection since they enable real-time monitoring and early detection of fire threats in an efficient way. However, compared to conventional surveillance systems, WSNs operate under a set of unique resource constraints, including limitations with respect to transmission range, energy supply and computational capability. Considering that long transmission distance is inevitable in harsh geographical features such as woodland and shrubland, energy-efficient designs of WSNs are crucial for effective forest fire monitoring and detection systems. In this paper, we propose a novel framework that harnesses the benefits of WSNs for forest fire monitoring and detection. The framework employs random deployment, clustered hierarchy network architecture and environmentally aware protocols. The goal is to accurately detect a fire threat as early as possible while maintaining a reasonable energy consumption level. ns-2-based simulation validates that the proposed framework outperforms the conventional schemes in terms of detection delay and energy consumption.

scholarly journals Energy Efficient Hierarchical Clustering Approaches in Wireless Sensor Networks: A Survey

2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Bilal Jan ◽  
Haleem Farman ◽  
Huma Javed ◽  
Bartolomeo Montrucchio ◽  
Murad Khan ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Hierarchical Clustering ◽  
Energy Efficient ◽  
Cluster Head ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Surveillance Systems ◽  
Grid Based

Wireless sensor networks (WSN) are one of the significant technologies due to their diverse applications such as health care monitoring, smart phones, military, disaster management, and other surveillance systems. Sensor nodes are usually deployed in large number that work independently in unattended harsh environments. Due to constraint resources, typically the scarce battery power, these wireless nodes are grouped into clusters for energy efficient communication. In clustering hierarchical schemes have achieved great interest for minimizing energy consumption. Hierarchical schemes are generally categorized as cluster-based and grid-based approaches. In cluster-based approaches, nodes are grouped into clusters, where a resourceful sensor node is nominated as a cluster head (CH) while in grid-based approach the network is divided into confined virtual grids usually performed by the base station. This paper highlights and discusses the design challenges for cluster-based schemes, the important cluster formation parameters, and classification of hierarchical clustering protocols. Moreover, existing cluster-based and grid-based techniques are evaluated by considering certain parameters to help users in selecting appropriate technique. Furthermore, a detailed summary of these protocols is presented with their advantages, disadvantages, and applicability in particular cases.

Smart Surveillance Systems

2014 ◽  
pp. 270-291 ◽  
Author(s):  
L. J. M. Rothkrantz
Keyword(s):  
Sensor Networks ◽  
Probabilistic Reasoning ◽  
Command And Control ◽  
Semantic Networks ◽  
Semantic Interpretation ◽  
Surveillance Systems ◽  
Military Operations ◽  
Control Centre ◽  
Human Operators ◽  
And Control

To enable effective and efficient command and control in military operations it is necessary to have full awareness of all the actions in the field. In traditional C2 systems, human operators play key roles varying from observation in the field up to semantic interpretation of observed data in the Command and Control Centre. Networks are mainly used to transmit data between different components of the network. Observation by human operators will be replaced by sensor networks. The huge amount of incoming data is far beyond the capacity of operators, so the heterogeneous, multimodal data from the different sensor systems has to be fused, aggregated, and filtered. Automated surveillance sensor networks are discussed in this chapter. Sensors are modelled as a distributed system of smart agents. Methods and technology from Artificial Intelligence such as expert systems, semantic networks, and probabilistic reasoning is used to give a semantic interpretation of the sensed data from the environment.

scholarly journals EM-Based High Speed Wireless Sensor Networks for Underwater Surveillance and Target Tracking

2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Kumudu Munasinghe ◽  
Mohammed Aseeri ◽  
Sultan Almorqi ◽  
Md. Farhad Hossain ◽  
Musbiha Binte Wali ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Target Tracking ◽  
Communication Systems ◽  
High Speed ◽  
Low Cost ◽  
Wireless Sensor ◽  
Surveillance Systems ◽  
Major Step ◽  
Data Rates

Underwater Wireless Sensor Networks (UWSNs) are considered as tangible, low cost solution for underwater surveillance and exploration. Existing acoustic wave-based UWSN systems fail to meet the growing demand for fast data rates required in military operations, oil/gas exploration, and oceanographic data collection. Electromagnetic (EM) wave-based communication systems, on the other hand, have great potential for providing high speed data rates in such scenarios. This paper will(1)discuss the challenges faced in the utilization of EM waves for the design of tactical underwater surveillance systems and(2)evaluate several EM wave-based three-dimensional (3D) UWSN architectures differing in topologies and/or operation principles on the performance of localization and target tracking. To the best of our knowledge, this is the first of its kind in the field of underwater communications where underwater surveillance techniques for EM wave-based high speed UWSNs have been investigated. Thus, this will be a major step towards achieving future high speed UWSNs.

Smart Surveillance Systems

Biometrics ◽  
2017 ◽  
pp. 1619-1642
Author(s):  
L. J. M. Rothkrantz
Keyword(s):  
Sensor Networks ◽  
Probabilistic Reasoning ◽  
Command And Control ◽  
Semantic Networks ◽  
Semantic Interpretation ◽  
Surveillance Systems ◽  
Military Operations ◽  
Control Centre ◽  
Human Operators ◽  
And Control

To enable effective and efficient command and control in military operations it is necessary to have full awareness of all the actions in the field. In traditional C2 systems, human operators play key roles varying from observation in the field up to semantic interpretation of observed data in the Command and Control Centre. Networks are mainly used to transmit data between different components of the network. Observation by human operators will be replaced by sensor networks. The huge amount of incoming data is far beyond the capacity of operators, so the heterogeneous, multimodal data from the different sensor systems has to be fused, aggregated, and filtered. Automated surveillance sensor networks are discussed in this chapter. Sensors are modelled as a distributed system of smart agents. Methods and technology from Artificial Intelligence such as expert systems, semantic networks, and probabilistic reasoning is used to give a semantic interpretation of the sensed data from the environment.

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