Information and Communication Technology as a Driver for Change in Agri‐food Chains

Poppe, K.J.; Wolfert, Sjaak; Verdouw, C.N.; Verwaart, Tim

doi:10.1111/1746-692x.12022

Cited by 63 publications

(84 citation statements)

References 4 publications

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“…and probability maps for diseases and disasters based on a dense network of weather and climate data will allow cultivation of crops in an optimal way. Site-specific information also enables new insurance (7) and business opportunities for the entire value chain, from technology and input suppliers to farmers, processors, and the retail sector (8) in developing and developed societies alike. If all farming-related data are recorded by automated sensors, the time needed for prioritizing the application of resources and for administrative surveillance is decreased.…”

Section: Ample Opportunitiesmentioning

confidence: 99%

Smart farming is key to developing sustainable agriculture

Walter¹,

Finger²,

Huber³

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

603

259

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Agriculture has seen many revolutions, whether the domestication of animals and plants a few thousand years ago, the systematic use of crop rotations and other improvements in farming practice a few hundred years ago, or the "green revolution" with systematic breeding and the widespread use of man-made fertilizers and pesticides a few decades ago. We suggest that agriculture is undergoing a fourth revolution triggered by the exponentially increasing use of information and communication technology (ICT) in agriculture.Autonomous, robotic vehicles have been developed for farming purposes, such as mechanical weeding, application of fertilizer, or harvesting of fruits. The development of unmanned aerial vehicles with autonomous flight control (1), together with the development of lightweight and powerful hyperspectral snapshot cameras that can be used to calculate biomass development and fertilization status of crops (2, 3), opens the field for sophisticated farm management advice. Moreover, decision-tree models are available now that allow farmers to differentiate between plant diseases based on optical information (4). Virtual fence technologies (5) allow cattle herd management based on remote-sensing signals and sensors or actuators attached to the livestock.Taken together, these technical improvements constitute a technical revolution that will generate disruptive changes in agricultural practices. This trend holds for farming not only in developed countries but also in developing countries, where deployments in ICT (e.g., use of mobile phones, access to the Internet) are being adopted at a rapid pace and could become the game-changers in the future (e.g., in the form of seasonal drought forecasts, climate-smart agriculture).Such profound changes in practice come not only with opportunities but also big challenges. It is crucial to point them out at an early stage of this revolution to avoid "lock-ins": advocates and skeptics of technology need to engage in an open dialogue on the future development of farming in the digital era. Only if aspects of technology, diversity of crop and livestock systems, and networking and institutions (i.e. markets and policies), are considered jointly in the dialogue, should farming in the digital era be termed "smart farming." Ample OpportunitiesSmart farming reduces the ecological footprint of farming. Minimized or site-specific application of inputs, such as fertilizers and pesticides, in precision agriculture systems will mitigate leaching problems as well as the emission of greenhouse gases (6). With current ICT, it is possible to create a sensor network allowing for almost continuous monitoring of the farm. Similarly, theoretical and practical frameworks to connect the states of plants, animals, and soils with the needs for production inputs, such as water, fertilizer, and medications, are in reach with current ICT globally.Smart farming can make agriculture more profitable for the farmer. Decreasing resource inputs will save the farmer money and labor, and increased reliabi...

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Section: Ample Opportunitiesmentioning

confidence: 99%

Smart farming is key to developing sustainable agriculture

Walter¹,

Finger²,

Huber³

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

603

259

View full text Add to dashboard Cite

show abstract

“…Aclimatesystem [6] ismeanttosupplyasuitablesurroundings for growing the plant by reading the temperature, humidity, lighting and major fact of co2 and therefore the amount of irrigationbyspecialsensors.Andmanagementoffactors.The proportion of lighting associated irrigation through an electrical device governed by a specific program automatically.ThemajorconcerningfactorisCarbondioxide in thisSystem.…”

Section: B Solutionstatementmentioning

confidence: 99%

Remote Sensing and Controlling of Co2 and Greenhouse Parameters Based on Iot

Chakradhar*,

Kumar,

Kishore

2020

IJRTE

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:The world global climate[6] change has caused unpredictable climatic conditions that have resulted within the international food shortage being knowledgeable about. A greenhouse can ordinarily turn out a lot of crops per square measure when put next to open field cultivation since the microclimatic parameters that confirm crop yieldareunendinglymonitoredAssociateinmanage and controlto confirm that an optimum surroundings is formed. The machinedriven greenhouse system achieves observation and management of a greenhouse[4] surroundings by exploitation sensors and actuators that are underneath the management of a microcontroller running a bug. The system consists of 2 stations. Remote observation station and therefore the Actuators/Sensors Station. The controller utilized in the actuators/ sensors station that ensures that the microclimatic parameters keep among pre-defined values as determined and set by the user is that the Arduino prototyping platform. The planned system is a remote sensing of agriculture parameters and system to the greenhouse agriculture. The arrange is to regulate greenhouse air, soil wet, temperature, and light, supported the soil wet the dominant action is accomplished for the greenhouse windows/doors supported crops once 1/4 complete around the year. The target is to extend the yield and to supply organic farming. The result shows the remote of greenhouse gas, soil wet, temperature, and light-weight for the inexperiencedhouse.

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“…The last mile humanitarian efforts can be based on microretailers as last mile nodes, especially in Asia, where it is possible to use social enterprises as coordinators of supply chains for the distribution of items for victims [16]. Technology-enabled cooperation based on Industry 4.0 innovations can help facilitate collaboration through the supply chain [17,18]. The supply chain operation reference (SCOR) can be applied for the metrics of logistics processes in the disaster area, but the metrics does not cover last mile options [19].…”

Section: Literature Reviewmentioning

confidence: 99%

Smart Scheduling: An Integrated First Mile and Last Mile Supply Approach

2018

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Supply chain management applies more and more Industry 4.0 innovations to increase their availability, elasticity, sustainability, and efficiency. In interconnected logistics networks, operations are integrated from suppliers through 3rd party logistics providers to customers. There are different delivery models depending on the time and cost. In the last few years, a wide range of customers is willing to pay an extra fee for the same delivery or instant delivery. This fact led to the increased importance of the optimized design and control of first mile/last mile (FMLM) delivery solutions. Cyberphysical system-based service innovations make it possible to enhance the productivity of FMLM delivery in the big data environment. The design and operation problems can be described as NP-hard optimization problems. These problems can be solved using sophisticated models and methods based on heuristic and metaheuristic algorithms. This research proposes an integrated supply model of FMLM delivery. After a careful literature review, this paper introduces a mathematical model to formulate the problem of realtime smart scheduling of FMLM delivery. The integrated model includes the assignment of first mile and last mile delivery tasks to the available resources and the optimization of operations costs, while constraints like capacity, time window, and availability are taken into consideration. Next, a black hole optimization-(BHO-) based algorithm dealing with a multiobjective supply chain model is presented. The sensitivity of the enhanced algorithm is tested with benchmark functions. Numerical results with different datasets demonstrate the efficiency of the proposed model and validate the usage of Industry 4.0 inventions in FMLM delivery.

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Information and Communication Technology as a Driver for Change in Agri‐food Chains

Cited by 63 publications

References 4 publications

Smart farming is key to developing sustainable agriculture

Smart farming is key to developing sustainable agriculture

Remote Sensing and Controlling of Co2 and Greenhouse Parameters Based on Iot

Smart Scheduling: An Integrated First Mile and Last Mile Supply Approach

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