Semantic Support for Scenarios to Improve Communication in Agribusiness

Organizations produce and exchange a lot of critical information to obtain good results. Systems developed in different domains are adapted to be integrated when they need to exchange information. Food and agribusiness are not the exceptions, they are pioneers in the use of massive data and collaboration. One of the biggest challenges to communicate software systems is analyzing their colliding context. Every software system relies on its own context, with its rules, dynamic, and language. It is a big effort to have a complete understanding of the composed domain. Scenarios are well-known tools to describe domains and are commonly described with text. When Scenarios are built by different stakeholders it is extremely important to review them in order to unify their description. Thus, the improved Scenarios with a unified point of view make it possible an analysis to identify the relationship between two different domains. This analysis is the key to design a mechanism to exchange information. This paper proposes a semantic definition of Scenarios and a set of queries to identify issues in the Scenarios and improve their quality. We also provide a wiki platform to implement the semantic support and the queries.Publicado en IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 568)

Decision Support Systems

Decision support systems (DSS) have evolved over the past four decades from theoretical concepts into real world computerized applications. DSS architecture contains three key components: knowledge base, computerized model, and user interface. DSS simulate cognitive decision-making functions of humans based on artificial intelligence methodologies (including expert systems, data mining, machine learning, connectionism, logistical reasoning, etc.) in order to perform decision support functions. The applications of DSS cover many domains, ranging from aviation monitoring, transportation safety, clinical diagnosis, weather forecast, business management to internet search strategy. By combining knowledge bases with inference rules, DSS are able to provide suggestions to end users to improve decisions and outcomes. This book is written as a textbook so that it can be used in formal courses examining decision support systems. It may be used by both undergraduate and graduate students from diverse computer-related fields. It will also be of value to established professionals as a text for self-study or for reference

An extension to scenarios to deal with business cases for the decision-making processes in the agribusiness domain

With the aim of pushing innovation through information and communication technology in the agri-business field, working closely with farmers is essential. It is especially important to systematically capture their knowledge in order to analyze, propose and design innovation artifacts (in terms of software applications). In this article, we use Scenarios to capture the knowledge of the experts that is elicited in early meetings previous to the definition of requirements. At those early stages, there are many uncertainties, and we are particularly interested in decision support. Thus, we propose an extension of the Scenarios for dealing with uncertainties. Scenarios are described in natural language, and it is very important to have an unbiased vocabulary. We complement Scenarios with a specific glossary, the Language Extended Lexicon that is also extended to decision support. According to V-model life cycle, every stage has a testing related stage. Thus, we also propose a set of rules to derive tests from the Scenarios. Summing up, we propose (i) an extension to Scenarios and the Language Extended Lexicon templates, (ii) a set of rules to derive tests, and (iii) an application to support the proposed technique. We have applied the proposed approach in a couple of case studies and we are confident that the results are promising. Nevertheless, we need to perform a further exhaustive validation.Laboratorio de Investigación y Formación en Informática Avanzad

The Digitalisation of African Agriculture Report 2018-2019

An inclusive, digitally-enabled agricultural transformation could help achieve meaningful livelihood improvements for Africa’s smallholder farmers and pastoralists. It could drive greater engagement in agriculture from women and youth and create employment opportunities along the value chain. At CTA we staked a claim on this power of digitalisation to more systematically transform agriculture early on. Digitalisation, focusing on not individual ICTs but the application of these technologies to entire value chains, is a theme that cuts across all of our work. In youth entrepreneurship, we are fostering a new breed of young ICT ‘agripreneurs’. In climate-smart agriculture multiple projects provide information that can help towards building resilience for smallholder farmers. And in women empowerment we are supporting digital platforms to drive greater inclusion for women entrepreneurs in agricultural value chains

Quality of life in rural areas: A topic for the rural development policy?

Contemporary transformations of rural areas involve changes in land uses, economic perspectives, connectivity, livelihoods, but also in lifestyles, whereupon a traditional view of ‘the rural’ and, consequently, of ‘rural development’ no longer holds. Accordingly, EU’s 2007-2013 Rural Development policy (RDP) is one framework to incorporate aspects labelled as quality of life (QOL) alongside traditional rural tenets. With a new rendition of the RDP underway, this paper scopes the content and extent of the expired RDP regarding its incorporation of QOL, in order to better identify considerations for future policy making. Using novel methodology called topic modelling, a series of latent semantic structures within the RDP could be unravelled and re-interpreted via a dual categorization system based on RDP’s own view on QOL, and on definitions provided by independent research. Corroborated by other audits, the findings indicate a thematic overemphasis on agriculture, with the focus on QOL being largely insignificant. Such results point to a rationale different than the assumed one, at the same time reinforcing an outdated view of rurality in the face of the ostensibly fundamental turn towards viewing rural areas in a wider, more humanistic, perspective. This unexpected issue of underrepresentation is next addressed through three possible drivers: conceptual (lingering productionist view of the rural), ideological (capitalist prerogative preventing non-pecuniary values from entering policy) and material (institutional lock-ins incapable of accommodating significant deviations from an agricultural focus). The paper ends with a critical discussion and some reflections on the broader concept of rurality

SUSTAINABLE VALUE OF RICE SUPPLY CHAIN: A SYSTEMATIC LITERATURE REVIEW AND RESEARCH AGENDA

The rice supply chain is important to achieve food security. It has various perspectives, challenges or issues that causes a complex problem in supply chain system. The existing problem are related to food availability, inventory level, fragmented distribution, affordability of prices, accessibility, variation of business processes and the environmental impact from production and logistics system. Moreover integration framework in the dimension of sustainability is limited. The objective of this article is to identify current problems to construct the idea of supply chain integration and to build the formulation for improvement the value of rice supply chain. Fifty articles discuss rice supply chain. The remaining discuss on increasing rice productivity, inventory optimization, performance improvement, and traceability. The VOS viewer result showed that sustainability is connected to the supply chain at a distant position which indicates that sustainability has the opportunity to be studied wider range in future research. The gap analysis showed that the production increase is limited to agronomy innovation and didn’t consider sustainable characteristics input. The indirect innovations that use information technology for precision farming also had not been comprehensively collaborated. The production absorption had not been considered in inventory optimization and traceability system had not been developed for supply availability. The improvement activities to fill the gap will transform supply chain performance more efficient, responsive and minimum environmental impacts for the enhancement of the sustainability value of the rice supply chain. Keywords: gap analysis,  integration, rice supply chain, sustainability, production and logistics syste

SUSTAINABLE VALUE OF RICE SUPPLY CHAIN: A SYSTEMATIC LITERATURE REVIEW AND RESEARCH AGENDA

The rice supply chain is important to achieve food security. It has various perspectives, challenges or issues that causes a complex problem in supply chain system. The existing problem are related to food availability, inventory level, fragmented distribution, affordability of prices, accessibility, variation of business processes and the environmental impact from production and logistics system. Moreover integration framework in the dimension of sustainability is limited. The objective of this article is to identify current problems to construct the idea of supply chain integration and to build the formulation for improvement the value of rice supply chain. Fifty articles discuss rice supply chain. The remaining discuss on increasing rice productivity, inventory optimization, performance improvement, and traceability. The VOS viewer result showed that sustainability is connected to the supply chain at a distant position which indicates that sustainability has the opportunity to be studied wider range in future research. The gap analysis showed that the production increase is limited to agronomy innovation and didn’t consider sustainable characteristics input. The indirect innovations that use information technology for precision farming also had not been comprehensively collaborated. The production absorption had not been considered in inventory optimization and traceability system had not been developed for supply availability. The improvement activities to fill the gap will transform supply chain performance more efficient, responsive and minimum environmental impacts for the enhancement of the sustainability value of the rice supply chain. Keywords: gap analysis,  integration, rice supply chain, sustainability, production and logistics syste

Making smallholder value chain partnerships inclusive: exploring digital farm monitoring through farmer friendly smartphone platforms

Open Access Journal; Published online: 04 Jun 2020Value chain partnerships face difficulties achieving inclusive relations, often leading to unsustainable collaboration. Improving information flow between actors has been argued to contribute positively to a sense of inclusion in such partnership arrangements. Smallholders however usually lack the capability to use advanced communication technologies such as smartphones which offer a means for elaborate forms of information exchange. This study explores to what extent co-designing smartphone platforms with smallholders for farm monitoring contributes to smallholder ability to communicate, and how this influences smallholder sense of inclusion. The study uses an Action Design Research approach in engaging smallholders in Ghana, through multi-stakeholder and focus group discussions, in a reflexive co-design process. The research finds that co-designing a platform interface was significant in improving farmer ability to comprehend and use smartphone based platforms for communicating farm conditions and their needs with value chain partners. Farmers were however skeptical of making demands based on the platform due to their lack of power and mistrust of other actors. This highlights a need for adjusting the social and political dimensions of partnership interactions, in tandem with the advancement of digital tools, in order to effectively facilitate a sense of inclusiveness in partnerships

Remote Health Monitoring IoT Framework using Machine Learning Prediction and Advanced Artificial Intelligence (AI) Model

Real intervention and treatment standards drew attention to remote health monitoring frameworks. Remote monitoring frameworks for disease detection at an early stage are opposed by most conventional works. Even so, it ran into issues like increased operational complexity, higher resource costs, inaccurate predictions, longer data collection times, and a lower convergence rate. A remote health monitoring framework that uses artificial intelligence (AI) to predict heart disease and diabetes from medical datasets is the goal of this project. Patients' health data is collected via smart devices, and the resulting data is then combined using a variety of nodes, including a detection node, a visualisation node, and a prognostic node. People with long-term illnesses (such as the elderly and disabled) are in such greater demand than ever before that a new approach to healthcare delivery is essential. In the evolved paradigm, conventional physical medical services foundations like clinics, nursing homes, and long haul care offices will be old. Due to recent advancements in modern technology, such as artificial intelligence (AI) and machine learning (ML), the smart healthcare system has become increasingly necessary (ML). This paper will discuss wearable and smartphone technologies, AI for medical diagnostics, and assistive structures, including social robots, that have been created for the surrounding upheld living climate. The review presents programming reconciliation structures that are urgent for consolidating information examination and other man-made consciousness instruments to develop brilliant medical care frameworks (AI)

AGROVOC: The linked data concept hub for food and agriculture

Newly acquired, aggregated and shared data are essential for innovation in food and agriculture to improve the discoverability of research. Since the early 1980′s, the Food and Agriculture Organization of the United Nations (FAO) has coordinated AGROVOC, a valuable tool for data to be classified homogeneously, facilitating interoperability and reuse. AGROVOC is a multilingual and controlled vocabulary designed to cover concepts and terminology under FAO's areas of interest. It is the largest Linked Open Data set about agriculture available for public use and its highest impact is through facilitating the access and visibility of data across domains and languages. This chapter has the aim of describing the current status of one of the most popular thesaurus in all FAO’s areas of interest, and how it has become the Linked Data Concept Hub for food and agriculture, through new procedures put in plac