An intelligent Edge-IoT platform for monitoring livestock and crops in a dairy farming scenario

Alonso, Ricardo S.; Sittón-Candanedo, Inés; García, Oscar N.; Prieto, Javier; González, Sara Rodríguez

doi:10.1016/j.adhoc.2019.102047

Cited by 214 publications

(153 citation statements)

References 45 publications

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“…Ricardo S. Alonso et al [132], designed an intelligent edge IoT based platform for precision livestock and crop monitoring in a dairy farming scenario. In their study, authors used the concepts of AI, blockchain technology, edge computing and IoT concepts for designing the platform.…”

Section: Iot In Crop Monitoringmentioning

confidence: 99%

Recent Developments of the Internet of Things in Agriculture: A Survey

2020

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A rise in the population has immensely increased the pressure on the agriculture sector. With the advent of technology, this decade is witnessing a shift from conventional approaches to the most advanced ones. The Internet of Things (IoT) has transformed both the quality and quantity of the agriculture sector. Hybridization of species along with the real-time monitoring of the farms paved a way for resource optimization. Scientists, research institutions, academicians, and most nations across the globe are moving towards the practice and execution of collaborative projects to explore the horizon of this field for serving mankind. The tech industry is racing to provide more optimal solutions. Inclusion of IoT, along with cloud computing, big data analytics, and wireless sensor networks can provide sufficient scope to predict, process, and analyze the situations and improve the activities in the real-time scenario. The concept of heterogeneity and interoperability of the devices by providing flexible, scalable, and durable methods, models are also opening new domains in this field. Therefore, this paper contributes towards the recent IoT technologies in the agriculture sector, along with the development of hardware and software systems. The public and private sector projects and startup's started all over the globe to provide smart and sustainable solutions in precision agriculture are also discussed. The current scenario, applications, research potential, limitations, and future aspects are briefly discussed. Based on the concepts of IoT a precision farming framework is also proposed in this article.

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Section: Iot In Crop Monitoringmentioning

confidence: 99%

Recent Developments of the Internet of Things in Agriculture: A Survey

2020

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“…Step 2: Basic parameters are adjusted in the decision tree , a vector consisting of md = [4,6,8,10] and min-split-gain=0. A grid search is then used to fine-tune the parameters in a specific range.…”

Section: A Simulation Configurationsmentioning

confidence: 99%

“…WSNs are a critical component in the internet of things (IOT) and have a variety of military and industrial applications [1]. They have been used for environmental monitoring [2], medical procedures [3], precision agriculture [4], animal tracking [5], remote sensing (during natural disasters) [6], explosives detection [7], and earthquake studies [8]. Although these application environments differ significantly, each requires accurate location information.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Approach Using Multistage Collaborative Calibration for Wireless Sensor Network Localization in 3D Environments

Liang

2020

IEEE Access

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Accurate localization is critical in the internet of things (IOT), especially for wireless sensor networks (WSNs). Location estimation can be affected by factors such as node density, topological diversity, and sensor coverage. As such, we propose a hybrid approach using multistage collaborative calibration for wireless sensor network localization, specifically in 3D environments. This technique integrates a Modified version of Light Gradient Boosting Model (MLGB), which is based on a regression scheme, a cooperative methodology, and a fine calibration model for collaborative fusion. These techniques were combined with quadrilateral shrunk centroid (QSC) and distance vector hop algorithms, using a multi-communication radius and an improved frog-leaping algorithm (DVMFL). In the first step, MLGB was used to correct for inhomogeneous localization estimation errors and RSSI data sparsity. As a result, the model is capable of adapting to high topological diversity (i.e., C-shape, H-shape, Sshape, and O-shape).Successive steps further improved prediction accuracy by using a screening cooperative anchor node strategy to increase node density and enhance the QSC-DVMFL fusion framework for fine position estimation. The proposed methodology was assessed in a series of validation, comparing it to other techniques. The results demonstrated a clear effectiveness and adaptability across a variety of factors that typically affect WSN localization. INDEX TERMS Wireless sensor network; Localization; Multistage collaborative calibration technique; Modified version of light GBM; Quadrilateral shrunk centroid;

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“…The concept of a smart irrigation system [26] is proposed in the Cloud-based Internet of Agriculture Things (IoAT) [27] in which sensors gather the findings of soil and transmit it towards the base station (BS) to take the required actions [28]. The major applications of IoT in smart automated agriculture include agricultural monitoring and control [29], controlled environment agriculture [30], open-field agriculture [31], livestock applications [32], food supply chain tracking [33], IoT middleware and interoperability [34,35], multi-layer deployments [36], and commercial solutions [37]. This shows the important role of digital innovation and technology that help in delivering high quality services to improve the urban expansion and migration to cities.…”

Section: Introductionmentioning

confidence: 99%

AgriTrust—A Trust Management Approach for Smart Agriculture in Cloud-based Internet of Agriculture Things

Awan

Din

Almogren

et al. 2020

Sensors

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Internet of Things (IoT) provides a diverse platform to automate things where smart agriculture is one of the most promising concepts in the field of Internet of Agriculture Things (IoAT). Due to the requirements of more processing power for computations and predictions, the concept of Cloud-based smart agriculture is proposed for autonomic systems. This is where digital innovation and technology helps to improve the quality of life in the area of urbanization expansion. For the integration of cloud in smart agriculture, the system is shown to have security and privacy challenges, and most significantly, the identification of malicious and compromised nodes along with a secure transmission of information between sensors, cloud, and base station (BS). The identification of malicious and compromised node among soil sensors communicating with the BS is a notable challenge in the BS to cloud communications. The trust management mechanism is proposed as one of the solutions providing a lightweight approach to identify these nodes. In this article, we have proposed a novel trust management mechanism to identify malicious and compromised nodes by utilizing trust parameters. The trust mechanism is an event-driven process that computes trust based on the pre-defined time interval and utilizes the previous trust degree to develop an absolute trust degree. The system also maintains the trust degree of a BS and cloud service providers using distinct approaches. We have also performed extensive simulations to evaluate the performance of the proposed mechanism against several potential attacks. In addition, this research helps to create friendlier environments and efficient agricultural productions for the migration of people to the cities.

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An intelligent Edge-IoT platform for monitoring livestock and crops in a dairy farming scenario

Cited by 214 publications

References 45 publications

Recent Developments of the Internet of Things in Agriculture: A Survey

Recent Developments of the Internet of Things in Agriculture: A Survey

A Hybrid Approach Using Multistage Collaborative Calibration for Wireless Sensor Network Localization in 3D Environments

AgriTrust—A Trust Management Approach for Smart Agriculture in Cloud-based Internet of Agriculture Things

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