Internet of Things in agriculture, recent advances and future challenges

Tzounis, A.; Katsoulas, Ν.; Bartzanas, Thomas; Kittas, C.

doi:10.1016/j.biosystemseng.2017.09.007

Cited by 653 publications

(403 citation statements)

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“…In farms, the use of technology to add intelligence to agriculture still has a vast potential to generate significant advances. Smart agriculture (or more broadly smart farming), depends on innovative technologies to increase the productivity of crops and animal products, to make efficient use of precious resources like water, and to decrease the amount of chemical substances used (e.g., medicines and pesticides) [5]. Notably, we have been involved in using IoT and machine learning solutions within the Sensors 2020, 20, 84 6 of 24 SWAMP project, which develops IoT-based approaches for smart water management for a precision irrigation application, and pilots them in Italy, Spain, and Brazil [4].…”

Section: Iot Smart Applicationsmentioning

confidence: 99%

“…Since smart applications will typically have to deal with thousands of devices-or considerably more-performance and scalability concerns are key to any successful IoT deployment. Yet, most current reported experiences show: (a) small-scale pilots [7,44]; (b) simulation-based or analytical results [21,45]; (c) measurement-based results with limited scope [19,46]; (d) no quantitative results at all [2,3,5,8,9,11,12,16,24,37,47]. Also, different architectural and deployment choices for IoT systems affect scalability, and real-time decision-making is possible in an environment composed of thousands of sensors [4,48].…”

Section: Performance and Scalability Of Iot Systemsmentioning

confidence: 99%

“…The number of devices connected to the Internet has been increasing steadily [1,2], so smart applications will typically have to deal with thousands or even millions of devices. Customized configurations, automated reconfigurability, and scalability are critical challenges in any successful deployment of IoT smart applications [3], in areas such as agriculture [4,5], cities [6,7], healthcare [8] and industry [9].…”

Section: Introductionmentioning

confidence: 99%

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Architecting and Deploying IoT Smart Applications: A Performance–Oriented Approach

Zyrianoff

Heideker

Silva

et al. 2019

Sensors

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Layered internet of things (IoT) architectures have been proposed over the last years as they facilitate understanding the roles of different networking, hardware, and software components of smart applications. These are inherently distributed, spanning from devices installed in the field up to a cloud datacenter and further to a user smartphone, passing by intermediary stages at different levels of fog computing infrastructure. However, IoT architectures provide almost no hints on where components should be deployed. IoT Software Platforms derived from the layered architectures are expected to adapt to scenarios with different characteristics, requirements, and constraints from stakeholders and applications. In such a complex environment, a one-size-fits-all approach does not adapt well to varying demands and may hinder the adoption of IoT Smart Applications. In this paper, we propose a 5-layer IoT Architecture and a 5-stage IoT Computing Continuum, as well as provide insights on the mapping of software components of the former into physical locations of the latter. Also, we conduct a performance analysis study with six configurations where components are deployed into different stages. Our results show that different deployment configurations of layered components into staged locations generate bottlenecks that affect system performance and scalability. Based on that, policies for static deployment and dynamic migration of layered components into staged locations can be identified.

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Section: Iot Smart Applicationsmentioning

confidence: 99%

Section: Performance and Scalability Of Iot Systemsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Architecting and Deploying IoT Smart Applications: A Performance–Oriented Approach

Zyrianoff

Heideker

Silva

et al. 2019

Sensors

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“…The IoT vision, key features, applications, and open issues were discussed in [24]. IoT in agriculture, its recent advances, and future challenges were outlined in [25].…”

Section: Related Workmentioning

confidence: 99%

Subsurface MIMO: A Beamforming Design in Internet of Underground Things for Digital Agriculture Applications

Salam

2019

JSAN

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In underground (UG) multiple-input and multiple-output (MIMO), transmit beamforming is used to focus energy in the desired direction. There are three different paths in the underground soil medium through which the waves propagate to reach the receiver. When the UG receiver receives a desired data stream only from the desired path, then the UG MIMO channel becomes a three-path (lateral, direct, and reflected) interference channel. Accordingly, the capacity region of the UG MIMO three-path interference channel, and the degrees of freedom (multiplexing gain of this MIMO channel) requires careful modeling. Therefore, expressions are required for the degrees of freedom of the UG MIMO interference channel. The underground receiver needs to perfectly cancel the interference from the three different components of the EM waves propagating in the soil medium. This concept is based upon reducing the interference of the undesired components to a minimum level at the UG receiver using the receive beamforming. In this paper, underground environment-aware MIMO using transmit and receive beamforming has been developed. The optimal transmit and receive beamforming, combining vectors under minimal intercomponent interference constraints, are derived. It is shown that UG MIMO performs best when all three components of the wireless UG channel are leveraged for beamforming. The environment-aware UG MIMO technique leads to three-fold performance improvements and paves the way for design and development of next-generation sensor-guided irrigation systems in the field of digital agriculture. Based on the analysis of underground radio-wave propagation in subsurface radio channels, a phased-array antenna design is presented that uses water content information and beam-steering mechanisms to improve efficiency and communication range of wireless underground communications. It is shown that the subsurface beamforming using phased-array antennas improves wireless underground communications by using the array element optimization and soil-air interface refraction adjustment schemes. This design is useful for subsurface communication system where sophisticated sensors and software systems are used as data collection tools that measure, record, and manage spatial and temporal data in the field of digital agriculture. systems to sense, analyze, detect, and manage the soil and farm-specific spatial and temporal patterns in the field for sustainability, profitability, and to protect the environment.The Internet of Underground Things (IOUT) have many applications in precision agriculture [1][2][3][4][5][6][7][8][9][10][11][12]. Border monitoring is another important application area of IOUT, where these networks are being used to enforce borders and stop infiltration [13,14]. Monitoring applications of IOUT include landslide monitoring and pipeline monitoring [5,15,16]. IOUT provides seamless access to information collected from agricultural fields through the Internet. IOUT includes in situ soil-sensing capabilities (e.g., soil moisture, temperat...

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“…Pendekatan IoT untuk konservasi seni akan melibatkan pemasangan node sensor kecil dan gateway untuk transfer data ke cloud [5]. Sistem yang mengunakan teknologi Internet of things mengunakan sensor wireless untuk proses data yang didapat oleh sensor sehingga menjadi informasi [1]. Konsep Internet of things dibagi menjadi 3 lapisan: lapisan persepsi(sensing), lapisan jaringan (transfer data) dan lapisan aplikasi (penyimpanan data) [2].…”

Section: Pendahuluanunclassified

Internet of Things Smart Agriculture on ZigBee: A Systematic Review

Hidayat¹

2017

InComTech

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AbstrakTeknologi WSN kini semakin meningkat diakhir-akhirnya dan banyak diterapkan diberbagai bidang. Salah satu dari penerapan WSN seperti pada Agiculture yang berbasis Internet of things. WSN ini contoh seperti ZigBee, penerapan ZigBee pada Agiculture sangat membantu pada berbagai bidang Agiculture dimulai dari system control irigasi, pemantauan iklim pada Agiculture serta pengendalian system control rantai makan pada system Agiculture. Internet of things ini mendukung system Agiculture untuk memberikan komunikasi pada sensor-sensor yang ada di Aguculture ini. Sistem Agiculture ini diharapkan bisa meningkatkan produktivitas maupun prediksi masalah yang ada di system pertanian. Systematic riview ini memberikan gambaran bahwa teknologi Internet of things di Agiculture sangat berpontensi baik karena dapat meningkat para petani dalam operasional produksi pangan maupun ternak.

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Internet of Things in agriculture, recent advances and future challenges

Cited by 653 publications

References 50 publications

Architecting and Deploying IoT Smart Applications: A Performance–Oriented Approach

Architecting and Deploying IoT Smart Applications: A Performance–Oriented Approach

Subsurface MIMO: A Beamforming Design in Internet of Underground Things for Digital Agriculture Applications

Internet of Things Smart Agriculture on ZigBee: A Systematic Review

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