A Review and Progress of Research on Autonomous Drone in Agriculture, Delivering Items and Geographical Information Systems (GIS)

Budiharto, Widodo; Chowanda, Andry; Gunawan, Alexander Agung Santoso; Irwansyah, Edy; Suroso, Jarot S.

doi:10.1109/wsce49000.2019.9041004

Cited by 37 publications

(17 citation statements)

References 4 publications

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“…The use of geographic information systems (GIS) in agriculture has grown in depth and popularity since the 1990s. Some study findings have been directly applied to agricultural productivity, yielding significant economic gains [5].…”

Section: Literature Reviewmentioning

confidence: 99%

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Drone-based Geographical Information System (GIS) Mapping of Cassava Pythoplasma Disease (CPD) for Precision Agriculture

Plata¹,

Panganiban²,

Alado³

et al. 2022

IJETAE

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The development of Drone-based Geographical Information System (GIS) Mapping of Cassava Pythoplasma Disease (CPD) for Precision Agriculture is intended to detect Cassava Phytoplasma Disease. Cassava phytoplasma disease (CPD) is a major danger to the country's cassava sector right now. The Philippines is one of the Asian countries that grow cassava as an agricultural commodity. This initiative delivers unique solutions to help Cassava farmers in the region solve their challenges. The researchers developed the system using the Rapid Application Development (RAD) Methodology as a guide. The system's process flow was conceptualized using Data Flow Diagramming. The methods used in the detection process are Pixel Intensity, Color Intensity, and Ratio and Coordinates Plotting using Raw Data and Featured Layer. The development of the Drone-based Geographical Information System (GIS) Mapping of Cassava Pythoplasma Disease (CPD) for Precision Agriculture is an effective and innovative tool in detecting CPD in order to prevent the spread of the disease. The implementation of the developed system addressed the current needs of the partner agency in monitoring and preventing the occurrence of the CPD in their cassava plantation. Visual Imaging of CPD Heat Map Using Arc GIS JavaScript API was an effective tool in detecting the presence of Cassava Phytoplasma disease in cassava plantation using the different techniques and methodologies Keywords — ARC GIS, Heat Map, JAVA Script, Visual Imaging, Web-based system

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Section: Literature Reviewmentioning

confidence: 99%

“…The authors investigated drone-assisted approaches such as pesticide sprayer implementation in agriculture and area mapping [5].…”

Section: Literature Reviewmentioning

confidence: 99%

Drone-based Geographical Information System (GIS) Mapping of Cassava Pythoplasma Disease (CPD) for Precision Agriculture

Plata¹,

Panganiban²,

Alado³

et al. 2022

IJETAE

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“…In addition, the utilization of drones has been addressed in the literature [ 25 , 26 ], [ 27 , 28 ] as an enabler for providing a reliable and cost-effective wireless communications solution for smart farming. By exploiting features such as autonomy, mobility, and adjustable altitude, drones can enhance a wireless network’s capacity, reliability, and energy efficiency [ 29 ].…”

Section: Related Workmentioning

confidence: 99%

LoRa Communications as an Enabler for Internet of Drones towards Large-Scale Livestock Monitoring in Rural Farms

Behjati

Noh

Alobaidy

et al. 2021

Sensors

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Currently, smart farming is considered an effective solution to enhance the productivity of farms; thereby, it has recently received broad interest from service providers to offer a wide range of applications, from pest identification to asset monitoring. Although the emergence of digital technologies, such as the Internet of Things (IoT) and low-power wide-area networks (LPWANs), has led to significant advances in the smart farming industry, farming operations still need more efficient solutions. On the other hand, the utilization of unmanned aerial vehicles (UAVs), also known as drones, is growing rapidly across many civil application domains. This paper aims to develop a farm monitoring system that incorporates UAV, LPWAN, and IoT technologies to transform the current farm management approach and aid farmers in obtaining actionable data from their farm operations. In this regard, an IoT-based water quality monitoring system was developed because water is an essential aspect in livestock development. Then, based on the Long-Range Wide-Area Network (LoRaWAN®) technology, a multi-channel LoRaWAN® gateway was developed and integrated into a vertical takeoff and landing drone to convey collected data from the sensors to the cloud for further analysis. In addition, to develop LoRaWAN®-based aerial communication, a series of measurements and simulations were performed under different configurations and scenarios. Finally, to enhance the efficiency of aerial-based data collection, the UAV path planning was optimized. Measurement results showed that the maximum achievable LoRa coverage when operating on-air via the drone is about 10 km, and the Longley–Rice irregular terrain model provides the most suitable path loss model for the scenario of large-scale farms, and a multi-channel gateway with a spreading factor of 12 provides the most reliable communication link at a high drone speed (up to 95 km/h). Simulation results showed that the developed system can overcome the coverage limitation of LoRaWAN® and it can establish a reliable communication link over large-scale wireless sensor networks. In addition, it was shown that by optimizing flight paths, aerial data collection could be performed in a much shorter time than industrial mission planning (up to four times in our case).

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“…(2) availability of real-time data for crowd dynamics modeling, with the help of powerful onboard processing units for estimating the crowd dynamics [6][7][8], and (3) lowering overall operational costs as the same monitoring device can be deployed elsewhere with an effective increase in its coverage [4], as well as reducing the human resource [5,9]. The benefits provided by drone use have already been established in other fields where mobility and aerial access tremendously increase visibility and site access such as in the maritime environment [10], agricultural technologies [11][12][13][14], mining industries [15], and disasters, tsunami, and pandemic management [16].…”

Section: Introductionmentioning

confidence: 99%

Unmanned Aerial Vehicles for Crowd Monitoring and Analysis

et al. 2021

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Crowd monitoring and analysis has become increasingly used for unmanned aerial vehicle applications. From preventing stampede in high concentration crowds to estimating crowd density and to surveilling crowd movements, crowd monitoring and analysis have long been employed in the past by authorities and regulatory bodies to tackle challenges posed by large crowds. Conventional methods of crowd analysis using static cameras are limited due to their low coverage area and non-flexible perspectives and features. Unmanned aerial vehicles have tremendously increased the quality of images obtained for crowd analysis reasons, relieving the relevant authorities of the venues’ inadequacies and of concerns of inaccessible locations and situation. This paper reviews existing literature sources regarding the use of aerial vehicles for crowd monitoring and analysis purposes. Vehicle specifications, onboard sensors, power management, and an analysis algorithm are critically reviewed and discussed. In addition, ethical and privacy issues surrounding the use of this technology are presented.

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A Review and Progress of Research on Autonomous Drone in Agriculture, Delivering Items and Geographical Information Systems (GIS)

Cited by 37 publications

References 4 publications

Drone-based Geographical Information System (GIS) Mapping of Cassava Pythoplasma Disease (CPD) for Precision Agriculture

Drone-based Geographical Information System (GIS) Mapping of Cassava Pythoplasma Disease (CPD) for Precision Agriculture

LoRa Communications as an Enabler for Internet of Drones towards Large-Scale Livestock Monitoring in Rural Farms

Unmanned Aerial Vehicles for Crowd Monitoring and Analysis

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