A Survey on the Role of IoT in Agriculture for the Implementation of Smart Livestock Environment

Farooq, Muhammad Shoaib; Sohail, Osama Omar; Abid, Adnan; Rasheed, Saim

doi:10.1109/access.2022.3142848

Cited by 70 publications

(29 citation statements)

References 110 publications

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“…This technology is expected to transform many aspects of our daily lives given the booming nature of research in this subject, both in academia and industry. The three-layered structure of the IoT model is determined by its functionalities and consists of a perception layer, a network layer, and an application layer [14]. As follows, this is further explained: − Perception layer: This is considering the main sense of the IoT.…”

Section: Iot Main Featuresmentioning

confidence: 99%

“…− Network layer: This layer represents the entire and main work of the IoT. It processes and forwards information which is received from the main perception layer to upper layer such as the application layer [14]. − Application layer: To actualize the IoT's advanced capabilities, this layer fuses the socio-business requirements for the technology.…”

Section: Iot Main Featuresmentioning

confidence: 99%

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A new algorithm to enhance security against cyber threats for internet of things application

Abujassar¹,

Sayed

Yaseen

2023

IJECE

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<p>One major problem is detecting the unsuitability of traffic caused by a distributed denial of services (DDoS) attack produced by third party nodes, such as smart phones and other handheld Wi-Fi devices. During the transmission between the devices, there are rising in the number of cyber attacks on systems by using negligible packets, which lead to suspension of the services between source and destination, and can find the vulnerabilities on the network. These vulnerable issues have led to a reduction in the reliability of networks and a reduction in consumer confidence. In this paper, we will introduce a new algorithm called rout attack with detection algorithm (RAWD) to reduce the affect of any attack by checking the packet injection, and to avoid number of cyber attacks being received by the destination and transferred through a determined path or alternative path based on the problem. The proposed algorithm will forward the real time traffic to the required destination from a new alternative backup path which is computed by it before the attacked occurred. The results have showed an improvement when the attack occurred and the alternative path has used to make sure the continuity of receiving the data to the main destination without any affection.</p>

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Section: Iot Main Featuresmentioning

confidence: 99%

Section: Iot Main Featuresmentioning

confidence: 99%

A new algorithm to enhance security against cyber threats for internet of things application

Abujassar¹,

Sayed

Yaseen

2023

IJECE

View full text Add to dashboard Cite

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“…This section presents the complete IoT-based architecture for smart farming [20,21]. The proposed architecture consists of four layers: farm perception layer, sensors and actuators layer, communication network layer, and application layer, as shown in Figure 1.…”

Section: Iot-based Architecture For Smart Farmingmentioning

confidence: 99%

LoRa Based IoT Platform for Remote Monitoring of Large-Scale Agriculture Farms in Chile

Ahmed

Gallardo

Zúñiga

et al. 2022

Sensors

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Nowadays, conventional agriculture farms lack high-level automated management due to the limited number of installed sensor nodes and measuring devices. Recent progress of the Internet of Things (IoT) technologies will play an essential role in future smart farming by enabling automated operations with minimum human intervention. The main objective of this work is to design and implement a flexible IoT-based platform for remote monitoring of agriculture farms of different scales, enabling continuous data collection from various IoT devices (sensors, actuators, meteorological masts, and drones). Such data will be available for end-users to improve decision-making and for training and validating advanced prediction algorithms. Unlike related works that concentrate on specific applications or evaluate technical aspects of specific layers of the IoT stack, this work considers a versatile approach and technical aspects at four layers: farm perception layer, sensors and actuators layer, communication layer, and application layer. The proposed solutions have been designed, implemented, and assessed for remote monitoring of plants, soil, and environmental conditions based on LoRaWAN technology. Results collected through both simulation and experimental validation show that the platform can be used to obtain valuable analytics of real-time monitoring that enable decisions and actions such as, for example, controlling the irrigation system or generating alarms. The contribution of this article relies on proposing a flexible hardware and software platform oriented on monitoring agriculture farms of different scales, based on LoRaWAN technology. Even though previous work can be found using similar technologies, they focus on specific applications or evaluate technical aspects of specific layers of the IoT stack.

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“…The IoT foresees the networking of a wide range of smart things in our environment that are capable of accumulating, processing, and communicating data [ 1 ]. The IoT is a widely used technology in automated network systems across the world that has had an impact on different areas, such as the agricultural, medical, transport, and automobile industries, and water monitoring in recent years [ 2 , 3 ].…”

Section: Introductionmentioning

confidence: 99%

A New Intrusion Detection System for the Internet of Things via Deep Convolutional Neural Network and Feature Engineering

Ullah

Ahmad

Khan

et al. 2022

Sensors

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The Internet of Things (IoT) is a widely used technology in automated network systems across the world. The impact of the IoT on different industries has occurred in recent years. Many IoT nodes collect, store, and process personal data, which is an ideal target for attackers. Several researchers have worked on this problem and have presented many intrusion detection systems (IDSs). The existing system has difficulties in improving performance and identifying subcategories of cyberattacks. This paper proposes a deep-convolutional-neural-network (DCNN)-based IDS. A DCNN consists of two convolutional layers and three fully connected dense layers. The proposed model aims to improve performance and reduce computational power. Experiments were conducted utilizing the IoTID20 dataset. The performance analysis of the proposed model was carried out with several metrics, such as accuracy, precision, recall, and F1-score. A number of optimization techniques were applied to the proposed model in which Adam, AdaMax, and Nadam performance was optimum. In addition, the proposed model was compared with various advanced deep learning (DL) and traditional machine learning (ML) techniques. All experimental analysis indicates that the accuracy of the proposed approach is high and more robust than existing DL-based algorithms.

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A Survey on the Role of IoT in Agriculture for the Implementation of Smart Livestock Environment

Cited by 70 publications

References 110 publications

A new algorithm to enhance security against cyber threats for internet of things application

A new algorithm to enhance security against cyber threats for internet of things application

LoRa Based IoT Platform for Remote Monitoring of Large-Scale Agriculture Farms in Chile

A New Intrusion Detection System for the Internet of Things via Deep Convolutional Neural Network and Feature Engineering

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