IoT in Agriculture: Designing a Europe-Wide Large-Scale Pilot

Brewster, Christopher; Roussaki, Ioanna; Kalatzis, Nikos; Doolin, Kevin; Ellis, Keith A.

doi:10.1109/mcom.2017.1600528

Cited by 258 publications

(105 citation statements)

References 6 publications

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“…There have been proposed systems in industry [6][7][8] as well as in academia [9][10][11][12] for animal health management in dairy farms. A study by Steeneveld and Hogeveen 13 and that by Andonovic et al 14 give an overview of the sensor systems available for health monitoring of animals in dairy farms.…”

Section: Literature Review Background and Motivationmentioning

confidence: 99%

SmartHerd management: A microservices‐based fog computing–assisted IoT platform towards data‐driven smart dairy farming

et al. 2019

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Summary Internet of Things (IoT), fog computing, cloud computing, and data‐driven techniques together offer a great opportunity for verticals such as dairy industry to increase productivity by getting actionable insights to improve farming practices, thereby increasing efficiency and yield. In this paper, we present SmartHerd, a fog computing–assisted end‐to‐end IoT platform for animal behavior analysis and health monitoring in a dairy farming scenario. The platform follows a microservices‐oriented design to assist the distributed computing paradigm and addresses the major issue of constrained Internet connectivity in remote farm locations. We present the implementation of the designed software system in a 6‐month mature real‐world deployment, wherein the data from wearables on cows is sent to a fog‐based platform for data classification and analysis, which includes decision‐making capabilities and provides actionable insights to farmer towards the welfare of animals. With fog‐based computational assistance in the SmartHerd setup, we see an 84% reduction in amount of data transferred to the cloud as compared with the conventional cloud‐based approach.

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Section: Literature Review Background and Motivationmentioning

confidence: 99%

SmartHerd management: A microservices‐based fog computing–assisted IoT platform towards data‐driven smart dairy farming

et al. 2019

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“…The challenges that has been identified are categorized based on the issues related to the technology, data management, social, privacy, security, ecological, ethical, standardization, policy and business models underlying the services [14]. It is also important that the technological set up grapples with issues concerning interoperability, connectivity, data processing power, clear data governance and available resources (e.g., software and hardware components) [13,15]. Friess and Riemenschneider [16] (p.10) have noted that the notion of LSPs needs to be broader than focusing only on validating technological approaches from a scalability and operational perspective but also to evaluate user experiences and reactions to IoT solutions.…”

Section: Literature Reviewmentioning

confidence: 99%

Adoption Barriers of IoT in Large Scale Pilots

et al. 2019

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The pervasive connectivity of devices enabled by Internet of Things (IoT) technologies is leading the way in various innovative services and applications. This increasing connectivity comes with its own complexity. Thus, large scale pilots (LSPs) are designed to develop, test and use IoT innovations in various domains in conditions very similar to their operational scalable setting. One of the key challenges facing the diffusion of such innovations within the course of an LSP is understanding the conditions in which their respective users decide to adopt them (or not). Accordingly, in this study we explore IoT adoption barriers in four LSPs in Europe from the following domains: smart cities, autonomous driving, wearables and smart agriculture and farming. By applying Roger's Diffusion of Innovation as a theoretical lens and using empirical data from workshops and expert interviews, we identify a set of common and domain specific adoption barriers. Our results reveal that trust, cost, perceived value, privacy and security are common concerns, yet shape differently across domains. In order to overcome various barriers, the relative advantage or value of using the innovation needs to be clearly communicated and related to the users' situational use; while this value can be economic in some domains, it is more hedonic in others. LSPs were particularly challenged in applying established strategies to overcome some of those barriers (e.g., co-creation with end-users) due to the immaturity of the technology as well as the scale of pilots. Accordingly, we reflect on the theoretical choice in the discussion as well as the implications of this study on research and practice. We conclude with providing practical recommendations to LSPs and avenues for future research.

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“…These statuses can be endlessly revived to the structure using IoT. The Internet of things (IOT) would be the internetworking [8] connected with brute machinery, transit, architecture and varying things embedded with equipment, programming, sensors, actuators, and framework organize that engage these articles to gather and exchange data. These contraptions hoard critical data with the help of various existing advances and after that uninhibitedly stream the data between various devices.…”

Section: B Implementationmentioning

confidence: 99%

Agricultural Data Transfer using IoT Technology

Vanitha¹

2019

IJRASET

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We know that the agricultural sector requires manual work for sure due to various reasons. Nowadays farmers are facing many problems to grow up the fruits and vegetables for us. This is because it is very difficult to know the conditions of land such as humidity, soil moisture and many more parameters without the physical presence of farmers at the agricultural farm. During the month of April, May; they find it very difficult to perform agricultural activities as the land dries within a certain period of time. So, here we are implementing a project which will give the whole data about the farm cultivation. By the help of these project farmers gets much relief in farm cultivation and the growth of crops will be not affected by these conditions also the farmer will be able to view the sensor details using IOT I. EXISTINGSYSTEM In the time of summer season it is very necessary to maintain the humidity and soil moisture. But sometimes is not understandable by the farmers. So due to this the crops which is growing gets dead or unhealthy. By this case the farmers faces much loss and many farmers suicide due to this loss. II.

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IoT in Agriculture: Designing a Europe-Wide Large-Scale Pilot

Cited by 258 publications

References 6 publications

SmartHerd management: A microservices‐based fog computing–assisted IoT platform towards data‐driven smart dairy farming

SmartHerd management: A microservices‐based fog computing–assisted IoT platform towards data‐driven smart dairy farming

Adoption Barriers of IoT in Large Scale Pilots

Agricultural Data Transfer using IoT Technology

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