An analysis of energy efficiency in Wireless Sensor Networks (WSNs) applied in smart agriculture

Banđur, Đoko; Jakšić, Branimir; Banđur, Miloš; Jović, Srđan

doi:10.1016/j.compag.2018.12.016

Cited by 69 publications

(27 citation statements)

References 20 publications

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“…An advantage of WSNs is their ability to easily define a network of devices that can be communicated with and gathered from a monitored field through communication links since the information is sent through multiple nodes with a gateway and connected to other networks like wireless Ethernet. Many researchers have applied WSNs to different research areas, such as environmental monitoring, forest fire detection, smart cities, smart education, healthcare, agricultural control, water quality monitoring, military uses, and asset management [1][2][3][4][5][6][7][8][9]. Accordingly, WSNs are suitable for multiple applications.…”

Section: Introductionmentioning

confidence: 99%

Smart Agriculture Using IoT Multi-Sensors: A Novel Watering Management System

Khoa

Man

Nguyen

et al. 2019

JSAN

108

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Advances in the Internet of Things (IoT) are helping to make water management smarter and optimizing consumption in the smart agriculture industry. This article proposes a new topology of sensor nodes based on the use of inexpensive and highly efficient components, such as water level, soil moisture, temperature, humidity, and rain sensors. Additionally, to guarantee good performance of the system, the used transmission module is based on LoRa LPWAN technology. The design of the main circuit board of the system is optimized by combining two layers and implementing software optimization. The overall sensor network is developed and tested in the research lab, and real farms can be controlled by users manually or automatically using the mobile application. Experimental results are produced by testing sensor and communication link effectiveness, and are subsequently validated in the field through a one-week measurement campaign.

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Section: Introductionmentioning

confidence: 99%

Smart Agriculture Using IoT Multi-Sensors: A Novel Watering Management System

Khoa

Man

Nguyen

et al. 2019

JSAN

108

View full text Add to dashboard Cite

show abstract

“…Wireless Sensor Network (WSN) consists of various sensing stations also called sensor nodes that are dispersed into the observing area to sense the desired data [ [1] , [2] , [3] , [4] ]. All the nodes are self-governing and operated independently in an ad-hoc manner with nominal cost.…”

Section: Introductionmentioning

confidence: 99%

Secure and energy-efficient framework using Internet of Medical Things for e-healthcare

Saba

Haseeb

Ahmed

2020

Journal of Infection and Public Health

132

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In various fields, the internet of things (IoT) gains a lot of popularity due to its autonomous sensors operations with the least cost. In medical and healthcare applications, the IoT devices develop an ecosystem to sense the medical conditions of the patients' such as blood pressure, oxygen level, heartbeat, temperature, etc. and take appropriate actions on an emergency basis. Using it, the healthcare-related data of patients is transmitted towards the remote users and medical centers for post-analysis. Different solutions have been proposed using Wireless Body Area Network (WBAN) to monitor the medical status of the patients based on low powered biosensor nodes, however, preventing increased energy consumption and communication costs are demanding and interesting problems. The issue of unbalanced energy consumption between biosensor nodes degrades the timely delivery of the patient's information to remote centers and gives a negative impact on the medical system. Moreover, the sensitive data of the patient is transmitting over the insecure Internet and prone to vulnerable security threats. Therefore, data privacy and integrity from malicious traffic are another challenging research issue for medical applications. This research article aims to a proposed secure and energy-efficient framework using Internet of Medical Things (IoMT) for e-healthcare (SEF-IoMT), which primary objective is to decrease the communication overhead and energy consumption between biosensors while transmitting the healthcare data on a convenient manner, and the other hand, it also secures the medical data of the patients against unauthentic and malicious nodes to improve the network privacy and integrity. The simulated results exhibit that the proposed framework improves the performance of medical systems for network throughput by 18%, packets loss rate by 44%, end-to-end delay by 26%, energy consumption by 29%, and link breaches by 48% than other states of the art solutions.

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“…Many applications around the world have been implementing different operations, based on the background of IoT, to offer novel services for smart cities [1][2][3] and optimize energetic efficiency. For examples, energy efficiency was considered in [4,5], cars were connected by IoT methods in [6][7][8], and water management in smart agriculture was investigated in [9][10][11][12][13], among a long list of other IoT application areas.…”

Section: Introductionmentioning

confidence: 99%

Waste Management System Using IoT-Based Machine Learning in University

Khoa

Phuc

Lam

et al. 2020

Wireless Communications and Mobile Computing

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Along with the development of the Internet of Things (IoT), waste management has appeared as a serious issue. Waste management is a daily task in urban areas, which requires a large amount of labour resources and affects natural, budgetary, efficiency, and social aspects. Many approaches have been proposed to optimize waste management, such as using the nearest neighbour search, colony optimization, genetic algorithm, and particle swarm optimization methods. However, the results are still too vague and cannot be applied in real systems, such as in universities or cities. Recently, there has been a trend of combining optimal waste management strategies with low-cost IoT architectures. In this paper, we propose a novel method that vigorously and efficiently achieves waste management by predicting the probability of the waste level in trash bins. By using machine learning and graph theory, the system can optimize the collection of waste with the shortest path. This article presents an investigation case implemented at the real campus of Ton Duc Thang University (Vietnam) to evaluate the performance and practicability of the system’s implementation. We examine data transfer on the LoRa module and demonstrate the advantages of the proposed system, which is implemented through a simple circuit designed with low cost, ease of use, and replace ability. Our system saves time by finding the best route in the management of waste collection.

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An analysis of energy efficiency in Wireless Sensor Networks (WSNs) applied in smart agriculture

Cited by 69 publications

References 20 publications

Smart Agriculture Using IoT Multi-Sensors: A Novel Watering Management System

Smart Agriculture Using IoT Multi-Sensors: A Novel Watering Management System

Secure and energy-efficient framework using Internet of Medical Things for e-healthcare

Waste Management System Using IoT-Based Machine Learning in University

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