A Overview on WSN Deployment and a Novel Conceptual BIM-based Approach in Smart Buildings

Zaimen, Khaoula; Brahmia, Mohamed-el-Amine; Dollinger, Jean-François; Moalic, Laurent; Abouaïssa, Abdelhafid; Idoumghar, Lhassane

doi:10.1109/iotsms52051.2020.9340226

Cited by 11 publications

(2 citation statements)

References 26 publications

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“…Khaoula, Z. et al (2020) [ 35 ] suggested a conceptual framework to maximize the sensing coverage, and lifetime and minimize the total deployment cost of WSN in the smart building by using the building information modeling (BIM) database, which includes all the required information about the building and uses the sensor parameters as input data to the proposed system; then, an evolutionary algorithm (genetic algorithm) will be used to solve the optimization problem. After that, this optimized solution will be visualized using the BIM plugin tool in an off-line and real-time 3D building model, considering heterogeneous sensors and different obstacles.…”

Section: Literature Reviewmentioning

confidence: 99%

Deployment Optimization Algorithms in Wireless Sensor Networks for Smart Cities: A Systematic Mapping Study

Abdulwahid

Mishra

2022

Sensors

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In recent years, different types of monitoring systems have been designed for various applications, in order to turn the urban environments into smart cities. Most of these systems consist of wireless sensor networks (WSN)s, and the designing of these systems has faced many problems. The first and most important problem is sensor node deployment. The main function of WSNs is to gather the required information, process it, and send it to remote places. A large number of sensor nodes were deployed in the monitored area, so finding the best deployment algorithm that achieves maximum coverage and connectivity with the minimum number of sensor nodes is the significant point of the research. This paper provides a systematic mapping study that includes the latest recent studies, which are focused on solving the deployment problem using optimization algorithms, especially heuristic and meta-heuristic algorithms in the period (2015–2022). It was found that 35% of these studies updated the swarm optimization algorithms to solve the deployment problem. This paper will be helpful for the practitioners and researchers, in order to work out new algorithms and seek objectives for the sensor deployment. A comparison table is provided, and the basic concepts of a smart city and WSNs are presented. Finally, an overview of the challenges and open issues are illustrated.

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Section: Literature Reviewmentioning

confidence: 99%

Deployment Optimization Algorithms in Wireless Sensor Networks for Smart Cities: A Systematic Mapping Study

Abdulwahid

Mishra

2022

Sensors

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“…A complete data source that can describe a building accurately and provide the necessary information (separators, plans, windows, materials, etc.) needed to model the target area is the Building Information Modeling (BIM) tool [55]. For outdoor environment, researchers use mainly the Digital Elevation Model (DEM) [46], [56], [57] and raster and vector modelings [58] which is a 3D representation of the terrain topology.…”

Section: A Indoor Environment Vs Outdoor Environmentmentioning

confidence: 99%

A Survey of Artificial Intelligence Based WSNs Deployment Techniques and Related Objectives Modeling

Zaimen¹,

Brahmia²,

Moalic

et al. 2022

IEEE Access

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Recent advances in hardware and communication technologies have accelerated the deployment of billions of wireless sensors. This transformation has created a wide range of applications adapted to the evolving trends of our daily life requirements. Wireless sensor networks (WSNs) could be deployed in several target areas including buildings, forests, oceans, and smart cities. Nevertheless, finding the optimal location for each sensor node is a challenging task, typically when the environment involves heterogeneous obstacles. Many approaches and methods have been proposed to deal with the problem of WSN deployment, each addressing one or more objectives and constraints, such as network coverage, lifetime, connectivity, and energy consumption. The purpose of this survey paper is to provide the needed background to understand and study the WSNs deployment problem with a focus on its two key aspects: the optimization model and the solving methods based on artificial intelligence (AI). Additionally, it covers recent works on WSNs deployment and identifies their advantages and limitations. Furthermore, simulation experiments were carried out to compare the performance of widely used algorithms in the context of WSNs deployment problem, primarily genetic algorithm, particle swarm optimization, flower pollination, and ant colony optimization. Finally, this paper discusses and highlights several open challenges and research issues that must be explored in the future.

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Lie hypergraph and chaos‐based privacy preserving protocol for wireless sensor networks in IoT environment

Sridharan,

Rajendran,

Venkatraman

2023

Int J Communication

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SummaryWireless sensor networks (WSN) are innately resource restrained and beneficial in a wide range of applications, including smart homes, e‐health care, law, military systems, disaster management, and emergency reprieve. These applications are linked to various devices that may communicate with one another through the internet, typically known as Internet of Things (IoT). The application of WSN plays an integral role in the IoT infrastructure. In a WSN, sensors are haphazardly placed in environments where the data transmission is challenged by privacy concerns. This paper proposes a methodology termed Lie hypergraph and chaos‐based secure routing (LH‐CSR) to perform an energy‐efficient routing with secure data transmission in WSN. In the first phase, the deployed sensor nodes are transformed into a hypergraph from which cluster head (CH) is elected by hypergraph transversal property, and for secure routing, the route is formed by the Lie commutators of the Lie algebra of upper triangular matrices. The second phase emphasizes privacy preservation by introducing the novel chaotic map formulation to process the key generation. The encryption and decryption processes are maintained by key generation to prevent data loss during retrieval. In this way, the data are retained confidentially with minimal computational overhead. The performance of the LH‐CSR is evaluated through a simulation, which shows that it outperforms over compared protocols in terms of cryptographic time, network lifetime, packet delivery ratio, end‐to‐end delay, and throughput.

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A Overview on WSN Deployment and a Novel Conceptual BIM-based Approach in Smart Buildings

Cited by 11 publications

References 26 publications

Deployment Optimization Algorithms in Wireless Sensor Networks for Smart Cities: A Systematic Mapping Study

Deployment Optimization Algorithms in Wireless Sensor Networks for Smart Cities: A Systematic Mapping Study

A Survey of Artificial Intelligence Based WSNs Deployment Techniques and Related Objectives Modeling

Lie hypergraph and chaos‐based privacy preserving protocol for wireless sensor networks in IoT environment

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