Internet of Things for the Future of Smart Agriculture: A Comprehensive Survey of Emerging Technologies

Friha, Othmane; Ferrag, Mohamed Amine; Shu, Lei; Μαγλαράς, Λέανδρος; Wang, Xiaochan

doi:10.1109/jas.2021.1003925

Cited by 270 publications

(81 citation statements)

References 197 publications

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“…Today, the traditional cloud-based architecture for agriculture systems is inefficient to satisfy all the requirements of the current scenarios [4], [5], [7], [8], as it lacks the essential efficiency prerequisites such as energy consumption, CO2 emission, network traffic, and so on [6]. Consequently, there is a need to develop an energy-efficient architecture for a smart agriculture system to fulfill these requirements.…”

Section: Proposed Architecture For Smart Agriculture Systemmentioning

confidence: 99%

“…IoT solutions are highly associated with cloud computing to process the huge amount of heterogeneous data sent or received by agriculture sensors/actuators [4]. Although cloud computing can handle smart agriculture applications, some of the applications and services produce a large amount of data and need to be processed in a real-time manner, which may cause a heavy load on the network, long response time, and poor quality of service, due to limited bandwidth [5]. Therefore, using the traditional cloud-based architecture may not be efficient to support these applications, which may also result in high energy consumption due to the transfer of agriculture data to and from the cloud.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, using the traditional cloud-based architecture may not be efficient to support these applications, which may also result in high energy consumption due to the transfer of agriculture data to and from the cloud. The Information and Communication Technology (ICT) industry is projected to account for 20% of the global electricity demand by 2025 [5]- [8], [9]. Usually, consuming electricity is accompanied by carbon emissions (CO2).…”

Section: Introductionmentioning

confidence: 99%

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Energy-Efficient Edge-Fog-Cloud Architecture for IoT-Based Smart Agriculture Environment

Alharbi

Aldossary

2021

IEEE Access

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The current agriculture systems compete to take advantage of industry advanced technologies, including the internet of things (IoT), cloud/fog/edge computing, artificial intelligence, and agricultural robots to monitor, track, analyze and process various functions and services in real-time. Additionally, these technologies can make the agricultural processes smarter and more cost-efficient by using automated systems and eliminating any human interventions, hence enhancing agricultural production to meet future expectations. Although the current agriculture systems that adopt the traditional cloud-based architecture have provided powerful computing infrastructure to distributed IoT sensors. However, the cost of energy consumption associated with transferring heterogeneous data over the multiple network tiers to process, analyze and store the sensor's information in the cloud has created a huge load on information and communication infrastructure. Besides, the energy consumed by cloud data centers has an environmental impact associated with using non-clean fuels, which usually release carbon emissions (CO2) to produce electricity. Thus, to tackle these issues, we propose a new integrated edge-fog-cloud architectural paradigm that promises to enhance the energy-efficient of smart agriculture systems and corresponding carbon emissions. This architecture allows data collection from several sensors to process and analyze the agriculture data that require real-time operation (e.g., weather temperature, soil moisture, soil acidity, irrigation, etc.) in several layers (edge, fog, and cloud). Thus, the real-time processing could be held by the edge and fog layers to reduce the load on the cloud layer, which will help to enhance the overall energy consumption and process the agriculture applications/services efficiently. Mathematical modeling is conducted using mixed-integer linear programming (MILP) for a smart agriculture environment, where the proposed architecture is implemented, and results are analyzed and compared to the traditional implementation. According to the results of thousands of agriculture sensors, the proposed architecture outperforms the traditional cloud-based architecture in terms of reducing the overall energy consumption by 36% and the carbon emissions by 43%. In addition to these achievements, the results show that our proposed architecture can reduce network traffic by up to 86%, which can reduce network congestion. Finally, we develop a heuristic algorithm to validate and mimic the presented approach, and it shows comparable results to the MILP model. INDEX TERMSSmart agriculture, edge-fog-cloud computing, internet of things, energy-efficiency, carbon emission. Hatem A. Alharbi received the B.Sc. degree in Computer Engineering (Hons.

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Section: Proposed Architecture For Smart Agriculture Systemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Energy-Efficient Edge-Fog-Cloud Architecture for IoT-Based Smart Agriculture Environment

Alharbi

Aldossary

2021

IEEE Access

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“…The IoT and remote sensing applications have recently been implemented to monitor and control indoor greenhouse parameters [8,9], to optimize the irrigation system automation [10], to monitor crop sensitive data and provide the farmer with real-time information about performance in order to take correct decisions [11], to detect plant diseases using image evaluation [12] and to control the lighting system [13] or nutrient optimal levels in the soil [14]. A review about IoT applications in smart agriculture appeared in reference [15].…”

Section: Introductionmentioning

confidence: 99%

Model Predictive Control versus Traditional Relay Control in a High Energy Efficiency Greenhouse

et al. 2021

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The sustainable agriculture cultivation in greenhouses is constantly evolving thanks to new technologies and methodologies able to improve the crop yield and to solve the common concerns which occur in protected environments. In this paper, an MPC-based control system has been realized in order to control the indoor air temperature in a high efficiency greenhouse. The main objective is to determine the optimal control signals related to the water mass flow rate supplied by a heat pump. The MPC model allows a predefined temperature profile to be tracked with an energy saving approach. The MPC has been implemented as a multiobjective optimization model that takes into account the dynamic behavior of the greenhouse in terms of energy and mass balances. The energy supply is provided by a ground coupled heat pump (GCHP) and by the solar radiation while the energy losses related to heat transfers across the glazed envelope. The proposed MPC method was applied in a smart innovative greenhouse located in Italy, and its performances were compared with a traditional reactive control method in terms of deviation of the indoor temperature in respect to the desired one and in terms of electric power consumption. The results demonstrated that, for a time horizon of 20 h, in a greenhouse with dimensions 15.3 and 9.9 m and an average height of 4.5 m, the proposed MPC approach saved about 30% in electric power compared with a relay control, guaranteeing a consistent and reliable temperature profile in respect to the predefined tracked one.

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“…The strong number generation is required not only for high-performance systems, but it is also a necessity for low-cost electronic systems where data security is critical; such as data logging, smart locks [25] and low data rate wireless communication systems for IoT [26]. On the other hand, for such low-cost embedded system applications in which the hardware resources are limited, it is a challenge to create a random number generator both strongly secure and resource-efficient [27,28].…”

Section: Introductionmentioning

confidence: 99%

Cryptographically strong random number generation using integrated CMOS photodiodes for low-cost microcontroller based applications

2021

Turk J Elec Eng & Comp Sci

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In this work, we propose a method to generate random numbers for low-cost, low-power, resource-limited low data-rate microcontrollers using integrated CMOS photodiodes. The proposed method utilizes an integrated CMOS photodiode in the photovoltaic mode as the entropy source. The method is based on serially capturing analog values derived from the integrated CMOS photodiode. The entropy of these values increased by a custom algorithm. The proposed random number generator is devised using an integrated CMOS photodiode manufactured in 180 nm standard CMOS technology. The wide applicably of the random number generator is demonstrated by realizing it on a lowcost Arduino UNO board placed in a typical room environment. The implemented random number generator passes NIST-SP800-22 and AIS31 randomness tests at high scores. The proposed method achieved 5.4Kbps throughput and 7.2% total significance level without any post-processing. The test results show the high cryptographical strength of the proposed method makes it a promising alternative to the currently used random number generation algorithms in low-cost low-resources low-data rate microcontroller-based applications.

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Internet of Things for the Future of Smart Agriculture: A Comprehensive Survey of Emerging Technologies

Cited by 270 publications

References 197 publications

Energy-Efficient Edge-Fog-Cloud Architecture for IoT-Based Smart Agriculture Environment

Energy-Efficient Edge-Fog-Cloud Architecture for IoT-Based Smart Agriculture Environment

Model Predictive Control versus Traditional Relay Control in a High Energy Efficiency Greenhouse

Cryptographically strong random number generation using integrated CMOS photodiodes for low-cost microcontroller based applications

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