Towards a Smart Farming Platform: From IoT-Based Crop Sensing to Data Analytics

Cadavid, Héctor; Garzón, Wilmer; Pérez, Alexander; Lopez, German Restrepo; Mendivelso, Cristian; Ramírez, Carlos

doi:10.1007/978-3-319-98998-3_19

Cited by 25 publications

(11 citation statements)

References 13 publications

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“…Many researchers have developed IoT architectures, but their efforts have tended to target specific areas of IoT/AI, i.e. sensors or weather monitoring systems [58,60,61]. This current paper is proposing a holistic IoT/AI platform to cover all areas within a SSA environment, performing the following tasks: (a) manage and govern data flow between SSA domains; (b) facilitate the integration of the different components of SSA architecture; (c) tackle interoperability issues caused by the utilization of different tools and software; (d) provide easy-to-use interfaces for interaction; (e) provide an ability to generate reports based on real-time data and keep it updated; (f) store generated data in sustainable storage place (i.e.…”

Section: B Proposed Iot/ai Ssa Platform As a Solutionmentioning

confidence: 99%

Smart Sustainable Agriculture (SSA) Solution Underpinned by Internet of Things (IoT) and Artificial Intelligence (AI)

Alreshidi¹

2019

IJACSA

119

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The Internet of Things (IoT) and Artificial Intelligence (AI) have been employed in agriculture over a long period of time, alongside other advanced computing technologies. However, increased attention is currently being paid to the use of such smart technologies. Agriculture has provided an important source of food for human beings over many thousands of years, including the development of appropriate farming methods for different types of crops. The emergence of new advanced IoT technologies has the potential to monitor the agricultural environment to ensure high-quality products. However, there remains a lack of research and development in relation to Smart Sustainable Agriculture (SSA), accompanied by complex obstacles arising from the fragmentation of agricultural processes, i.e. the control and operation of IoT/AI machines; data sharing and management; interoperability; and large amounts of data analysis and storage. This study firstly, explores existing IoT/AI technologies adopted for SSA and secondly, identifies IoT/AI technical architecture capable of underpinning the development of SSA platforms. As well as contributing to the current body of knowledge, this research reviews research and development within SSA and provides an IoT/AI architecture to establish a Smart, Sustainable Agriculture platform as a solution.

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Section: B Proposed Iot/ai Ssa Platform As a Solutionmentioning

confidence: 99%

Smart Sustainable Agriculture (SSA) Solution Underpinned by Internet of Things (IoT) and Artificial Intelligence (AI)

Alreshidi¹

2019

IJACSA

119

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“…The periodicity may go down to one minute. − Variety: gathered data can be in heterogeneous formats (photo, excel file, and graph) [19]. − Veracity: agricultural data must be correct and accurate for applying analytics process.…”

Section: Big Data Concept In Irrigationmentioning

confidence: 99%

Digital agriculture based on big data analytics: a focus on predictive irrigation for smart farming in Morocco

Rabhi

Falih

Afraites

et al. 2021

IJEECS

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Due to the spead of objects connected to the internet and objects connected to each other, agriculture nowadays knows a huge volume of data exchanged called big data. Therefore, this paper discusses connected agriculture or agriculture 4.0 instead of a traditional one. As irrigation is one of the foremost challenges in agriculture, it is also moved from manual watering towards smart watering based on big data analytics where the farmer can water crops regularly and without wastage even remotely. The method used in this paper combines big data, remote sensing and data mining algorithms (neural network and support vector machine). In this paper, we are interfacing the databricks platform based on the apache Spark tool for using machine learning to predict the soil drought based on detecting the soil moisture and temperature.

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“…To validate the design, a computer simulation was used to simulate the detection of the potato pest, Phytophthora infestans. The Smith Period prediction model was utilized, and simulations were run on 25 sensors spread over five different crops [15]. Vashisht et al studied a low-cost IoT platform for agriculture that makes use of TVWS to connect high-bandwidth sensors (lowcost, long-range technology).…”

Section: IIImentioning

confidence: 99%

“…Deploying innovative summarizing tools for sensor data and drone films are also made possible by accessing data acquired from several types of sensors. IoT-enabled Smart Agriculture Private Platform [15] has been developed. Telemetry, intelligent systems, wireless communications, and cloud computing should all be part of the solution that's being presented.…”

Section: Introductionmentioning

confidence: 99%

IoT-based Precision Agriculture Platform: A Review

Solanki¹

2021

IJRASET

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Technological advancements such as the Internet of Things (IoT) and Artificial Intelligence (AI) are helping to boost the global agricultural sector as it is expected to grow by around seventy percent in the next two decades. There are sensor-based systems in place to keep track of the plants and the surrounding environment. This technology allows farmers to watch and control farm operations from afar, but it has a few limitations. For farmers, these technologies are prohibitively expensive and demand a high level of technological competence. Besides, Climate change has a significant impact on crops because increased temperatures and changes in precipitation patterns increase the likelihood of disease outbreaks, resulting in crop losses and potentially irreversible plant destruction. Because of recent advancements in IoT and Cloud Computing, new applications built on highly innovative and scalable service platforms are now being developed. The use of Internet of Things (IoT) solutions has enormous promise for improving the quality and safety of agricultural products. Precision farming's telemonitoring system relies heavily on Internet of Things (IoT) platforms; therefore, this article quickly reviews the most common IoT platforms used in precision agriculture, highlighting both their key benefits and drawbacks

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Towards a Smart Farming Platform: From IoT-Based Crop Sensing to Data Analytics

Cited by 25 publications

References 13 publications

Smart Sustainable Agriculture (SSA) Solution Underpinned by Internet of Things (IoT) and Artificial Intelligence (AI)

Smart Sustainable Agriculture (SSA) Solution Underpinned by Internet of Things (IoT) and Artificial Intelligence (AI)

Digital agriculture based on big data analytics: a focus on predictive irrigation for smart farming in Morocco

IoT-based Precision Agriculture Platform: A Review

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