A Review of Applications and Communication Technologies for Internet of Things (IoT) and Unmanned Aerial Vehicle (UAV) Based Sustainable Smart Farming

Islam, Nahina; Rashid, Md. Mamunur; Pasandideh, Faezeh; Ray, Biplob; Moore, Steven T.; Kadel, Rajan

doi:10.3390/su13041821

Cited by 148 publications

(81 citation statements)

References 85 publications

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“…For example, the current figure of 2.1 billion tons of annual cereal production should reach approximately 3 billion tons [3]. This means there is a serious need to enhance productivity and meet the demands of nations [4]. However, the current agricultural land is restricted by various factors such as land and climate patterns, population density, and rapid urbanization, which are constantly posing threats to the availability of arable land [5].…”

Section: Introductionmentioning

confidence: 99%

A Low-Cost Platform for Environmental Smart Farming Monitoring System Based on IoT and UAVs

et al. 2021

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When integrating the Internet of Things (IoT) with Unmanned Aerial Vehicles (UAVs) occurred, tens of applications including smart agriculture have emerged to offer innovative solutions to modernize the farming sector. This paper aims to present a low-cost platform for comprehensive environmental parameter monitoring using flying IoT. This platform is deployed and tested in a real scenario on a farm in Medenine, Tunisia, in the period of March 2020 to March 2021. The experimental work fulfills the requirements of automated and real-time monitoring of the environmental parameters using both under- and aboveground sensors. These IoT sensors are on a farm collecting vast amounts of environmental data, where it is sent to ground gateways every 1 h, after which the obtained data is collected and transmitted by a drone to the cloud for storage and analysis every 12 h. This low-cost platform can help farmers, governmental, or manufacturers to predict environmental data over the geographically large farm field, which leads to enhancement in crop productivity and farm management in a cost-effective, and timely manner. Obtained experimental results infer that automated and human-made sets of actions can be applied and/or suggested, due to the innovative integration between IoT sensors with the drone. These smart actions help in precision agriculture, which, in turn, intensely boost crop productivity, saving natural resources.

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Section: Introductionmentioning

confidence: 99%

A Low-Cost Platform for Environmental Smart Farming Monitoring System Based on IoT and UAVs

et al. 2021

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“…The authors also covered the impact of climate on smart farming. Islam et al in [ 51 ] explored different use cases of smart farming, advantages, and applications of implementing IoT and UAVs in agriculture. The authors also discussed open research issues such as hardware maintenance and limited energy resources, security and privacy issues, big data in smart farming, weed detection and management, multi/hyper-spectral imagery for disease and pest control, and automated watering control and management in remote areas.…”

Section: Recent Reviews On Smart Agriculturementioning

confidence: 99%

A Systematic Survey on the Role of Cloud, Fog, and Edge Computing Combination in Smart Agriculture

Kalyani

Collier

2021

Sensors

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Cloud Computing is a well-established paradigm for building service-centric systems. However, ultra-low latency, high bandwidth, security, and real-time analytics are limitations in Cloud Computing when analysing and providing results for a large amount of data. Fog and Edge Computing offer solutions to the limitations of Cloud Computing. The number of agricultural domain applications that use the combination of Cloud, Fog, and Edge is increasing in the last few decades. This article aims to provide a systematic literature review of current works that have been done in Cloud, Fog, and Edge Computing applications in the smart agriculture domain between 2015 and up-to-date. The key objective of this review is to identify all relevant research on new computing paradigms with smart agriculture and propose a new architecture model with the combinations of Cloud–Fog–Edge. Furthermore, it also analyses and examines the agricultural application domains, research approaches, and the application of used combinations. Moreover, this survey discusses the components used in the architecture models and briefly explores the communication protocols used to interact from one layer to another. Finally, the challenges of smart agriculture and future research directions are briefly pointed out in this article.

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“…As long-range wireless communication systems, real-time transmission of measurement signals obtained using sensors has various applications in terms of smart farming [ 54 ], disaster alerts [ 55 ], water monitoring [ 56 ], food traceability [ 57 ], health diagnosis of social infrastructure such as bridges and tunnels [ 58 ], and smart homes [ 59 ]. Low-power long-range communication devices are increasingly anticipated for application for various Internet of things (IoT) devices and communication systems [ 60 ].…”

Section: Related Studiesmentioning

confidence: 99%

Development of Drone-Mounted Multiple Sensing System with Advanced Mobility for In Situ Atmospheric Measurement: A Case Study Focusing on PM2.5 Local Distribution

Madokoro

Kiguchi

Nagayoshi

et al. 2021

Sensors

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This study was conducted using a drone with advanced mobility to develop a unified sensor and communication system as a new platform for in situ atmospheric measurements. As a major cause of air pollution, particulate matter (PM) has been attracting attention globally. We developed a small, lightweight, simple, and cost-effective multi-sensor system for multiple measurements of atmospheric phenomena and related environmental information. For in situ local area measurements, we used a long-range wireless communication module with real-time monitoring and visualizing software applications. Moreover, we developed four prototype brackets with optimal assignment of sensors, devices, and a camera for mounting on a drone as a unified system platform. Results of calibration experiments, when compared to data from two upper-grade PM2.5 sensors, demonstrated that our sensor system followed the overall tendencies and changes. We obtained original datasets after conducting flight measurement experiments at three sites with differing surrounding environments. The experimentally obtained prediction results matched regional PM2.5 trends obtained using long short-term memory (LSTM) networks trained using the respective datasets.

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A Review of Applications and Communication Technologies for Internet of Things (IoT) and Unmanned Aerial Vehicle (UAV) Based Sustainable Smart Farming

Cited by 148 publications

References 85 publications

A Low-Cost Platform for Environmental Smart Farming Monitoring System Based on IoT and UAVs

A Low-Cost Platform for Environmental Smart Farming Monitoring System Based on IoT and UAVs

A Systematic Survey on the Role of Cloud, Fog, and Edge Computing Combination in Smart Agriculture

Development of Drone-Mounted Multiple Sensing System with Advanced Mobility for In Situ Atmospheric Measurement: A Case Study Focusing on PM2.5 Local Distribution

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