Smallholder Agriculture in the Information Age

Zheleva, Mariya; Bogdanov, Petko; Zois, Daphney-Stravoula; Xiong, Wei; Chandra, Ranveer; Kimball, Mark

doi:10.1145/3080556.3080563

Cited by 14 publications

(10 citation statements)

References 97 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Interoperability issues are strictly connected to data standards since a lack of industry-wide data exchange protocols causes difficulties in data exchange, thus limiting farm-level MIS applicability (Allen and Wolfert, 2011; Fountas et al , 2015a; Kruize et al , 2016). Another aspect related to technological features refers to concerns regarding data ownership, privacy and security, representing issues for users and possible adopters (Allen and Wolfert, 2011; Fountas et al , 2009; Kaloxylos et al , 2014; Zheleva et al , 2017).…”

Section: Resultsmentioning

confidence: 99%

Management information system adoption at the farm level: evidence from the literature

Giua

Materia

Camanzi

2020

BFJ

View full text Add to dashboard Cite

PurposeThis paper reviews the academic contributions that have emerged to date on the broad definition of farm-level management information systems (MISs). The purpose is twofold: (1) to identify the theories used in the literature to study the adoption of digital technologies and (2) to identify the drivers of and barriers to the adoption of such technologies.Design/methodology/approachThe literature review was based on a comprehensive review of contributions published in the 1998–2019 period. The search was both automated and manual, browsing through references of works previously found via high-quality digital libraries.FindingsDiffusion of innovations (DOIs) is the most frequently used theoretical framework in the literature reviewed, though it is often combined with other innovation adoption theories. In addition, farms’ and farmers’ traits, together with technological features, play a key role in explaining the adoption of these technologies.Research limitations/implicationsSo far, research has positioned the determinants of digital technology adoption mainly within the boundaries of the farm.Practical implicationsOn the practical level, the extensive determinants’ review has potential to serve the aim of policymakers and technology industries, to clearly and thoroughly understand adoption dynamics and elaborate specific strategies to deal with them.Originality/valueThis study’s contribution to the existing body of knowledge on the farm-level adoption of digital technologies is twofold: (1) it combines smart farming and existing technologies within the same category of farm-level MIS and (2) it extends the analysis to studies which not only focus directly on adoption but also on software architecture design and development.

show abstract

Section: Resultsmentioning

confidence: 99%

Management information system adoption at the farm level: evidence from the literature

Giua

Materia

Camanzi

2020

BFJ

View full text Add to dashboard Cite

show abstract

“…Ethnographic study of two Taiwanese farmers who follow permaculture principles (2018). ( 8) Smallholder Farms [79]. Field work to develop technical requirements for data sensing and data networks on farms (2017).…”

Section: Interlude and Methodsmentioning

confidence: 99%

“…Smallholder Farms [79]. To produce more food, more efficiently, and with less environmental impact requires that farming operations be modeled in realtime.…”

Section: Project Portraitsmentioning

confidence: 99%

Transition Discourse, Food, and Computing within Limits

Hendry¹

2021

LIMITS Workshop on Computing Within Limits

View full text Add to dashboard Cite

The limits workshop series is a transition system, which shapes the work of activists, educators, and researchers. It does so, in part, by the development of language and tools and by catalyzing conversations about reality and possible futures. Given this proposition and drawing on ontologically oriented analysis and design, I explore the transition discourse of eight limits' papers, which consider aspects of food. The papers represent competing views of the future of place and planet. Building on this review, I discuss worldviews and transitions, transitions and time, and I explore how formative and instrumental approaches in computing research can contribute to institutional and cultural adaptation.

show abstract

“…They follow the technique to process and analyze previously collected data and perform offline analysis, which is not suitable for real‐time tracking and monitoring of dynamic entities such as dairy cows. The gaps with the existing research are that either it has been developed out of the agricultural context or address the issue of network connectivity, analytics, and control in isolation; this has also been identified as key limitations by Zheleva et al…”

Section: Literature Review Background and Motivationmentioning

confidence: 99%

“…They follow the technique to process and analyze previously collected data and perform offline analysis, which is not suitable for real-time tracking and monitoring of dynamic entities such as dairy cows. The gaps with the existing research are that either it has been developed out of the agricultural context or address the issue of network connectivity, analytics, and control in isolation; this has also been identified as key limitations by Zheleva et al 45 Another recent survey by Jukan et al 46 identifies the lack of interoperability provided by such systems and identify the need of developing an integrated system combining edge, fog, and cloud to provide application and services. The authors here also identify that technology solutions with no consideration of interoperability results in vendor lock-in, which not only hinders innovation but also results in higher costs for the farmer/user.…”

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

View full text Add to dashboard Cite

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.

show abstract

Smallholder Agriculture in the Information Age

Cited by 14 publications

References 97 publications

Management information system adoption at the farm level: evidence from the literature

Management information system adoption at the farm level: evidence from the literature

Transition Discourse, Food, and Computing within Limits

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

Contact Info

Product

Resources

About