Wireless Sensor Networks in IPM

2020 ◽  
pp. 28-52
Author(s):  
Mina Petrić ◽  
Cedric Marsboom ◽  
Jurgen Vandendriessche
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Best Practice ◽  
Numerical Models ◽  
Wireless Sensor ◽  
Sensor Technology ◽  
Time Data ◽  
Vector Surveillance ◽  
Crop Agriculture ◽  
The Impact

An emerging field for environmental wireless sensor networks (WSN) is entomological vector surveillance. Sensor technology can be used to shoulder ecologically friendly practices within the integrated pest management (IPM) approach. Proper surveillance and subsequent modelling of the impact that pest and disease have on human health and crop agriculture is a pressing issue in numerous segments. Complex numerical models are being developed to generate information regarding the population dynamics of vector species and the expected circulation of vector-borne disease (VBD). These models require detailed micrometeorological forcing representative of the vector habitat to generate accurate simulations. Near real-time data offload in remote areas with flexible channels of communication for complex and heterogeneous topographies is an important component in this type of application. In this chapter, the authors provide an overview of the scope and best-practice approaches in applying WSN technology to drive IPM models.

scholarly journals On the Impact of Local Processing for Motor Monitoring Systems in Industrial Environments Using Wireless Sensor Networks

2013 ◽  
Vol 9 (7) ◽  
pp. 471917 ◽  
Author(s):  
Ruan Delgado Gomes ◽  
Marcéu Oliveira Adissi ◽  
Abel Cavalcante Lima-Filho ◽  
Marco Aurélio Spohn ◽  
Francisco Antônio Belo
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Wireless Sensor ◽  
Local Processing ◽  
Monitoring Systems ◽  
Industrial Environments ◽  
The Impact

scholarly journals Cryptanalysis and Security Enhancement of Three Authentication Schemes in Wireless Sensor Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Wenting Li ◽  
Bin Li ◽  
Yiming Zhao ◽  
Ping Wang ◽  
Fushan Wei
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Access ◽  
Academic Community ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Time Data ◽  
Forward Secrecy ◽  
User Friendliness ◽  
Authentication Mechanism

Nowadays wireless sensor networks (WSNs) have drawn great attention from both industrial world and academic community. To facilitate real-time data access for external users from the sensor nodes directly, password-based authentication has become the prevalent authentication mechanism in the past decades. In this work, we investigate three foremost protocols in the area of password-based user authentication scheme for WSNs. Firstly, we analyze an efficient and anonymous protocol and demonstrate that though this protocol is equipped with a formal proof, it actually has several security loopholes been overlooked, such that it cannot resist against smart card loss attack and violate forward secrecy. Secondly, we scrutinize a lightweight protocol and point out that it cannot achieve the claimed security goal of forward secrecy, as well as suffering from user anonymity violation attack and offline password guessing attack. Thirdly, we find that an anonymous scheme fails to preserve two critical properties of forward secrecy and user friendliness. In addition, by adopting the “perfect forward secrecy (PFS)” principle, we provide several effective countermeasures to remedy the identified weaknesses. To test the necessity and effectiveness of our suggestions, we conduct a comparison of 10 representative schemes in terms of the underlying cryptographic primitives used for realizing forward secrecy.

Adaptive Modeling of Routing Algorithms for Wireless Sensor Networks

2012 ◽  
pp. 73-92
Author(s):  
Marcello Cinque ◽  
Catello Di Martino
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Routing Algorithms ◽  
Experimental Results ◽  
Wireless Sensor ◽  
Adaptive Modeling ◽  
Modeling Approach ◽  
Viable Solution ◽  
The Impact

Recent years have witnessed a proliferation of routing algorithms for Wireless Sensor Networks (WSNs), hence complicating the choice of the proper algorithm to be used for a given application. Simulation frameworks represent a viable solution to anticipate crucial choices, however existing solutions do not encompass the impact of changes (e.g., route updates, node crashes) on the nodes behavior and vice-versa. This article proposes a novel adaptive modeling approach to master the complexity of the thorough simulation of routing algorithms for WSN. Experimental results are provided showing the effectiveness of the proposed approach at managing changes, and dealing with detailed aspects, during the simulation and comparison of several routing algorithms.

scholarly journals Performance Evaluation and Interference Characterization of Wireless Sensor Networks for Complex High-Node Density Scenarios

Proceedings ◽  
2018 ◽  
Vol 4 (1) ◽  
pp. 28
Author(s):  
Mikel Celaya-Echarri ◽  
Leyre Azpilicueta ◽  
Peio Lopez-Iturri ◽  
Erik Aguirre ◽  
Francisco Falcone
Keyword(s):  
Wireless Sensor Networks ◽  
Wave Propagation ◽  
Sensor Networks ◽  
Radio Wave ◽  
Radio Wave Propagation ◽  
Outdoor Environment ◽  
Wireless Sensor ◽  
5 Ghz ◽  
The Impact ◽  
Indoor And Outdoor

The uncontainable future development of smart regions, as a set of smart cities’ assembled networks, is directly associated with a growing demand of full interactive and connected ubiquitous smart environments. To achieve this goal of global connection, a large number of transceivers and multiple wireless systems will be involved to provide user services and applications (i.e., Ambient Assisted Living, emergency situations, e-health monitoring, or Intelligent Transportation Systems) anytime and anyplace, regardless of the devices, networks, or systems used. Adequate, efficient, and effective radio wave propagation tools, methodologies, and analyses in complex environments (indoor and outdoor) are crucial to prevent communication limitations such as coverage, capacity, speed, or channel interferences due to nodes’ density or channel restrictions. In this work, radio wave propagation characterization in an urban indoor and outdoor environment, at ISM 2.4 GHZ and 5 GHz Wireless Sensor Networks (WSNs), has been assessed. The selected scenario is an auditorium placed in a free open area surrounded by inhomogeneous vegetation. User density within the scenario, in terms of inherent transceivers density, poses challenges to the overall system operation, given by multiple node operation which increases overall interference levels. By means of an in-house developed 3D ray launching algorithm, the impact of variable density wireless sensor network operation within this complex scenario is presented. This analysis and the proposed simulation methodology can lead in an adequate interference characterization, considering conventional transceivers as well as wearables, which provide suitable information for the overall network performance in complex crowded indoor and outdoor scenarios.

scholarly journals Proposed Intelligent Pre-Processing Model of Real-Time Flood Forecasting and Warning for Data Classification and Aggregation

2017 ◽  
Vol 13 (11) ◽  
pp. 4 ◽  
Author(s):  
Marouane El Mabrouk ◽  
Salma Gaou
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Real Time ◽  
Wireless Sensors ◽  
Data Classification ◽  
Flood Forecasting ◽  
Base Stations ◽  
Wireless Sensor ◽  
Time Data ◽  
Forecasting And Warning

A wireless sensor network is a network that can design a self-organizing structure and provides effective support for several protocols such as routing, locating, discovering services, etc. It is composed of several nodes called sensors grouped together into a network to communicate with each other and with the base stations. Nowadays, the use of Wireless sensor networks increased considerably. It can collect physical data and transform it into a digital values in real-time to monitor in a continuous manner different disaster like flood. However, due to various factors that can affect the wireless sensor networks namely, environmental, manufacturing errors hardware and software problems etc... It is necessary to carefully select and filter the data from the wireless sensors since we are providing a decision support system for flood forecasting and warning. In this paper, we presents an intelligent Pre-Processing model of real-time flood forecasting and warning for data classification and aggregation. The proposed model consists on several stages to monitor the wireless sensors and its proper functioning, to provide the most appropriate data received from the wireless sensor networks in order to guarantee the best accuracy in terms of real-time data and to generate a historical data to be used in the further flood forecasting.

ANALYSIS AND EVALUATION OF RANDOM PLACEMENT STRATEGIES IN WIRELESS SENSOR NETWORKS

2014 ◽  
Vol 23 (10) ◽  
pp. 1450138 ◽  
Author(s):  
THAIER HAYAJNEH ◽  
SAMER KHASAWNEH
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Performance ◽  
Quality Measures ◽  
Wireless Sensor ◽  
Hybrid Strategy ◽  
Deployment Strategy ◽  
Area Of Interest ◽  
Random Placement ◽  
The Impact

Wireless sensor networks (WSNs) are an attractive choice for many applications where sensors are densely and efficiently deployed in an area of interest. For example, in surveillance applications, where deterministic placement is not applicable, the sensors have to be randomly deployed entirely or partially in an area. Whether random or deterministic, the strategy of deploying the sensors has a large impact on the performance of WSNs. In this paper, we propose a systematic methodology for sensors placement based on several random distributions. The quality of deployment is evaluated using a set of proposed measures, the significance of which highly depends on the WSN application. The impact of these deployment strategies on the network performance is thoroughly studied. Moreover, we propose a new hybrid deployment strategy that aims to achieve the best performance based on the suggested deployment quality measures. Both the placement strategies with the deployment quality measures are evaluated using extensive simulations. The results show that the proposed hybrid strategy outperformed other strategies including uniform, random, Gaussian, and exponential distributions. In addition, the paper identifies the family of applications where each of the quality measures is highly critical.

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