AgriFusion: An Architecture for IoT and Emerging Technologies Based on a Precision Agriculture Survey

Singh, R. A.; Berkvens, Rafael; Weyn, Maarten

doi:10.1109/access.2021.3116814

Cited by 86 publications

(36 citation statements)

References 167 publications

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“…The type of soil compost is related to soil analysis. For this, sensors and computer tomography [ 104 , 105 ] can support measuring soil nutrients and provide images of the field properties in the coffee field. Invariably, a technological platform has to be used to collect data and develop recommendations for producers through an application on cell phones.…”

Section: Resultsmentioning

confidence: 99%

Roadmapping 5.0 Technologies in Agriculture: A Technological Proposal for Developing the Coffee Plant Centered on Indigenous Producers’ Requirements from Mexico, via Knowledge Management

Contreras-Medina

Medina–Cuéllar

Rodríguez-García

2022

Plants

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The coffee plant, with more than 40 billion shrubs, 9 million tons of grains produced, and 80% of its production accounted for by small-scale producers, has been severely damaged since the emergence of Hemileia vastatrix and Hypothenemus hampei. Despite technological support, these pests have caused 20% to 40% production losses, a 50% to 60% deficit in performance, and a cost of between USD 70 million and USD 220 million to the world economies, which forces us to rethink actions centered on people as the key elements to develop appropriate solutions. For this, the present study presents a technological proposal centered on small indigenous coffee producer requirements for introducing Industry 5.0 technologies, considering roadmapping, knowledge management, statistical analysis, and the social, productive, and digital contexts of five localities in Mexico. The results show a correlation between monitoring and control, soil analysis, the creation of organic fertilizers, accompaniment, and coffee experimentation, as the actions to be implemented, proposing the introduction of a mobile application; sensors, virtual platforms, dome-shaped greenhouses, and spectrophotometric technology as relevant technologies centered on indigenous coffee producers’ requirements. This study is important for policymakers, academics, and producers who wish to develop strategies centered on people in Mexico and the world.

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Section: Resultsmentioning

confidence: 99%

Roadmapping 5.0 Technologies in Agriculture: A Technological Proposal for Developing the Coffee Plant Centered on Indigenous Producers’ Requirements from Mexico, via Knowledge Management

Contreras-Medina

Medina–Cuéllar

Rodríguez-García

2022

Plants

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show abstract

“…Solutions proposed for irrigation applications were reviewed in [13], [14] by considering the parameters typically monitored in such applications such as water quantity and quality, soil characteristics, weather conditions, and fertilizer usage. Papers [15], [16] are comprehensive surveys that discussed the emerging technologies which support smart water management solutions for precision agriculture such as ML and AI, fog or edge computing, Software Defined Networks, Big Data, and Nanotechnology. A broader review of literature was conducted in [17] by outlining the research work done in smart water management systems as implemented in urban contexts (i.e., residential and industrial), emphasizing on supply and distribution networks.…”

Section: A Related Workmentioning

confidence: 99%

IoT-Based Water Management Systems: Survey and Future Research Direction

et al. 2022

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The Internet of Things (IoT) sustainable solutions are the next generation of methods for managing and monitoring valuable natural resources such as water. Research has focused on smart IoT-based water management and monitoring system designs for various types of applications, including agricultural, industrial, residential, and crude oil exploration sectors. To this end, unlike other surveys available in the literature, this work presents an all-encompassing analysis of 43 papers published between 2014 and 2022 for systems proposed to manage and monitor water in four different sectors: the agricultural, industrial, residential, and the oilfield sectors. In this work, we also propose a new optical water management system to address a gap in the literature, particularly for oilfield processes that require significant amounts of water to stimulate oil production. The proposed system employs an advanced optical technique for sensing and transmitting collected data. Overall, this work provides a seminal guide for future research efforts focused on integrating IoT in the field of water management and monitoring.

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“…The system is built on wireless sensor network technology. A solution architecture is proposed in [12] for designing key performance indicators (KPIs) in precision agriculture (PA). An IoT-based smart farming system and an effective prediction approach dubbed WPART (Wrapper feature in PART classification technique) based on machine learning techniques to forecast crop productivity and drought for effective decision-support in IoT-based smart farming systems were recommended in [13].…”

Section: Introductionmentioning

confidence: 99%

Machine learning and IoT-based smart farming for enhancing the crop yield

Sundaresan¹,

Johnson²,

Bharathy³

et al. 2023

J. Phys.: Conf. Ser.

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The lack of favourable atmospheric conditions leads to the loss of many crops each year. In India alone, over 11 billion dollars are lost. By combining IoT and machine learning technologies, this team has created a system that integrates agriculture’s three primary operations: crop selection, autonomous watering, and fertiliser suggestion. The following crops—Apple, Rice, Maize, Grape, Banana, Orange, Cotton, and Coffee—were considered in the study. Three systems are covered in the paper: The crop recommendation system employs machine learning to examine factors including nitrogen (N), phosphorous (P), potassium (K), pH, and weather before recommending a crop. The crop type and the current levels of soil nutrients are the two main determinants on which the fertiliser recommendation method bases its recommendation. When employing an automatic irrigation system, the crop is irrigated automatically while taking current soil moisture levels and weather forecasts into consideration. This paper attempted to implement the mentioned systems. The paper discusses the successes of the crop recommendation system, the automatic watering system, and the fertiliser recommendation system. In this paper, we report the results of simulations of the mentioned systems.

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AgriFusion: An Architecture for IoT and Emerging Technologies Based on a Precision Agriculture Survey

Cited by 86 publications

References 167 publications

Roadmapping 5.0 Technologies in Agriculture: A Technological Proposal for Developing the Coffee Plant Centered on Indigenous Producers’ Requirements from Mexico, via Knowledge Management

Roadmapping 5.0 Technologies in Agriculture: A Technological Proposal for Developing the Coffee Plant Centered on Indigenous Producers’ Requirements from Mexico, via Knowledge Management

IoT-Based Water Management Systems: Survey and Future Research Direction

Machine learning and IoT-based smart farming for enhancing the crop yield

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