A Reference Model for Monitoring IoT WSN-Based Applications

Capella, J.V.; Campelo, José Carlos; Bonastre, Alberto; Ors, R.

doi:10.3390/s16111816

Cited by 35 publications

(19 citation statements)

References 35 publications

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“…The interaction with the network and services layer is achieved using an intermediate layer of management logic [36]. WSN data will be stored in an online database [37].…”

Section: The Management Layermentioning

confidence: 99%

Precision Agriculture: A Remote Sensing Monitoring System Architecture

2019

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Smart Farming is a development that emphasizes on the use of modern technologies in the cyber-physical field management cycle. Technologies such as the Internet of Things (IoT) and Cloud Computing have accelerated the digital transformation of the conventional agricultural practices promising increased production rate and product quality. The adoption of smart farming though is hampered because of the lack of models providing guidance to practitioners regarding the necessary components that constitute IoT-based monitoring systems. To guide the process of designing and implementing Smart farming monitoring systems, in this paper we propose a generic reference architecture model, taking also into consideration a very important non-functional requirement, the energy consumption restriction. Moreover, we present and discuss the technologies that incorporate the seven layers of the architecture model that are the Sensor Layer, the Link Layer, the Encapsulation Layer, the Middleware Layer, the Configuration Layer, the Management Layer and the Application Layer. Furthermore, the proposed Reference Architecture model is exemplified in a real-world application for surveying Saffron agriculture in Kozani, Greece.

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“…The interaction with the network and services layer is achieved using an intermediate layer of management logic [36]. WSN data will be stored in an online database [37].…”

Section: The Management Layermentioning

confidence: 99%

Precision Agriculture: A Remote Sensing Monitoring System Architecture

2019

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“…ε fs and ε amp are required energy for amplification of transmitted signal to transmit one bit in open space and multipath models respectively; l denotes the number of bits of data; d is the distance between two nodes; E t (d,l) is the energy consumption of the sending end; E r (l) is the energy consumption of the receiving end. The residual energy [6] of each node is calculated by Equation 3:…”

Section: Energy Consumption Modelmentioning

confidence: 99%

“…In order to assist other nodes in the network to build information links, nodes can be used as router or terminal or both of them [3,4]. Mobile Ad hoc sensor network can be utilized in these scenarios, such as military and habitat monitoring [5,6], target tracking network [7,8]. For example, in the animal tracking system, sensor nodes are loaded on the body of animals in order to observing animal behavior.…”

Section: Introductionmentioning

confidence: 99%

A Robust and Energy-Efficient Weighted Clustering Algorithm on Mobile Ad Hoc Sensor Networks †

Liu

Xiao

et al. 2018

Algorithms

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In an Ad hoc sensor network, nodes have characteristics of limited battery energy, self-organization and low mobility. Due to the mobility and heterogeneity of the energy consumption in the hierarchical network, the cluster head and topology are changed dynamically. Therefore, topology control and energy consumption are growing to be critical in enhancing the stability and prolonging the lifetime of the network. In order to improve the survivability of Ad hoc network effectively, this paper proposes a new algorithm named the robust, energy-efficient weighted clustering algorithm (RE2WCA). For the homogeneous of the energy consumption; the proposed clustering algorithm takes the residual energy and group mobility into consideration by restricting minimum iteration times. In addition, a distributed fault detection algorithm and cluster head backup mechanism are presented to achieve the periodic and real-time topology maintenance to enhance the robustness of the network. The network is analyzed and the simulations are performed to compare the performance of this new clustering algorithm with the similar algorithms in terms of cluster characteristics, lifetime, throughput and energy consumption of the network. The result shows that the proposed algorithm provides better performance than others.

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“…Such autonomous and embedded sensors equipped with wireless interconnectivity capabilities [12,13,14] are expected to play a key role in the development of future Internet of Things (IoT) applications [15,16]. More specifically, the demonstration case in this work is focused on monitoring the ageing process of coolant fluids [17,18] in industrial metal processing of metallic cylinders (pistons) used in hydraulic elevators in the industrial collaborator Kleemann S.A. (Kilkis, Greece).…”

Section: Introductionmentioning

confidence: 99%

Characterization of Industrial Coolant Fluids and Continuous Ageing Monitoring by Wireless Node—Enabled Fiber Optic Sensors

Sachat

Meristoudi

Markos

et al. 2017

Sensors

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Environmentally robust chemical sensors for monitoring industrial processes or infrastructures are lately becoming important devices in industry. Low complexity and wireless enabled characteristics can offer the required flexibility for sensor deployment in adaptable sensing networks for continuous monitoring and management of industrial assets. Here are presented the design, development and operation of a class of low cost photonic sensors for monitoring the ageing process and the operational characteristics of coolant fluids used in an industrial heavy machinery infrastructure. The chemical, physical and spectroscopic characteristics of specific industrial-grade coolant fluids were analyzed along their entire life cycle range, and proper parameters for their efficient monitoring were identified. Based on multimode polymer or silica optical fibers, wide range (3–11) pH sensors were developed by employing sol-gel derived pH sensitive coatings. The performances of the developed sensors were characterized and compared, towards their coolants’ ageing monitoring capability, proving their efficiency in such a demanding application scenario and harsh industrial environment. The operating characteristics of this type of sensors allowed their integration in an autonomous wireless sensing node, thus enabling the future use of the demonstrated platform in wireless sensor networks for a variety of industrial and environmental monitoring applications.

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A Reference Model for Monitoring IoT WSN-Based Applications

Cited by 35 publications

References 35 publications

Precision Agriculture: A Remote Sensing Monitoring System Architecture

Precision Agriculture: A Remote Sensing Monitoring System Architecture

A Robust and Energy-Efficient Weighted Clustering Algorithm on Mobile Ad Hoc Sensor Networks †

Characterization of Industrial Coolant Fluids and Continuous Ageing Monitoring by Wireless Node—Enabled Fiber Optic Sensors

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