Agricultural information dissemination using ICTs: a review and analysis of information dissemination models in China

Open Access funded by China Agricultural UniversityOver the last three decades, China’s agriculture sector has been transformed from the traditional to modern practice through the effective deployment of Information and Communication Technologies (ICTs). Information processing and dissemination have played a critical role in this transformation process. Many studies in relation to agriculture information services have been conducted in China, but few of them have attempted to provide a comprehensive review and analysis of different information dissemination models and their applications. This paper aims to review and identify the ICT based information dissemination models in China and to share the knowledge and experience in applying emerging ICTs in disseminating agriculture information to farmers and farm communities to improve productivity and economic, social and environmental sustainability. The paper reviews and analyzes the development stages of China’s agricultural information dissemination systems and different mechanisms for agricultural information service development and operations. Seven ICT-based information dissemination models are identified and discussed. Success cases are presented. The findings provide a useful direction for researchers and practitioners in developing future ICT based information dissemination systems. It is hoped that this paper will also help other developing countries to learn from China’s experience and best practice in their endeavor of applying emerging ICTs in agriculture information dissemination and knowledge transfer

The Impact of Human Error in the Use of Agricultural Tractors: A Case Study Research in Vineyard Cultivation in Italy

Recently, standards and regulations concerning occupational safety have become more and more rigorous. Nevertheless, the number of accidents and victims has not decreased significantly, as reported by official statistics. In Italy, the agricultural sector is certainly one of the most affected by this situation, especially taking into account the occurrence of serious injuries and fatalities related to the use of tractors. The main reasons for such a situation can be ascribed to the peculiarities of agricultural operations. Therefore, when analyzing the root causes of agricultural accidents, a user-centered approach is needed in order to make the development of health and safety interventions easier and more effective. Based on this, the present paper proposes a practical case study research focused on integrating the factor of human error into the risk assessment procedures of agricultural activities in vineyard cultivation. Such an approach allowed us to consider the impact of human errorwhile performing work activities (e.g., the use of a tractor)on hazards and related hazardous events in a thorough manner. The proposed approach represents a novelty in the sector of the safety assessment of agricultural activities, providing a first valuable basis for further analysis and implementation by researchers and practitioners

AI and OR in management of operations: history and trends

The last decade has seen a considerable growth in the use of Artificial Intelligence (AI) for operations management with the aim of finding solutions to problems that are increasing in complexity and scale. This paper begins by setting the context for the survey through a historical perspective of OR and AI. An extensive survey of applications of AI techniques for operations management, covering a total of over 1200 papers published from 1995 to 2004 is then presented. The survey utilizes Elsevier's ScienceDirect database as a source. Hence, the survey may not cover all the relevant journals but includes a sufficiently wide range of publications to make it representative of the research in the field. The papers are categorized into four areas of operations management: (a) design, (b) scheduling, (c) process planning and control and (d) quality, maintenance and fault diagnosis. Each of the four areas is categorized in terms of the AI techniques used: genetic algorithms, case-based reasoning, knowledge-based systems, fuzzy logic and hybrid techniques. The trends over the last decade are identified, discussed with respect to expected trends and directions for future work suggested

A fuzzy-QFD approach for the enhancement of work equipment safety: a case study in the agriculture sector

The paper proposes a design for safety methodology based on the use of the Quality Function Deployment (QFD) method, focusing on the need to identify and analyse risks related to a working task in an effective manner, i.e. considering the specific work activities related to such a task. To reduce the drawbacks of subjectivity while augmenting the consistency of judgements, the QFD was augmented by both the Delphi method and the fuzzy logic approach. To verify such an approach, it was implemented through a case study in the agricultural sector. While the proposed approach needs to be validated through further studies in different contexts, its positive results in performing hazard analysis and risk assessment in a comprehensive and thorough manner can contribute practically to the scientific knowledge on the application of QFD in design for safety activities

Environmental risk assessment in a contaminated estuary: an integrated weight of evidence approach as a decision support tool

Environmental risk assessment of complex ecosystems such as estuaries is a challenge, where innovative and integrated approaches are needed. The present work aimed at developing an innovative integrative methodology to evaluate in an impacted estuary (the Sado, in Portugal, was taken as case study), the adverse effects onto both ecosystem and human health. For the purpose, new standardized lines of evidence based on multiple quantitative data were integrated into a weight of evidence according to a best expert judgment approach. The best professional judgment for a weight of evidence approach in the present study was based on the following lines of evidence: i) human contamination pathways; ii) human health effects: chronic disease; iii) human health effects: reproductive health; iv) human health effects: health care; v) human exposure through consumption of local agriculture produce; vi) exposure to contaminated of water wells and agriculture soils; vii) contamination of the estuarine sedimentary environment (metal and organic contaminants); viii) effects on benthic organisms with commercial value; and ix) genotoxic potential of sediments. Each line of evidence was then ordinally ranked by levels of ecological or human health risk, according to a tabular decision matrix and expert judgment. Fifteen experts scored two fishing areas of the Sado estuary and a control estuarine area, in a scale of increasing environmental risk and management actions to be taken. The integrated assessment allowed concluding that the estuary should not be regarded as impacted by a specific toxicant, such as metals and organic compounds hitherto measured, but by the cumulative risk of a complex mixture of contaminants. The proven adverse effects on species with commercial value may be used to witness the environmental quality of the estuarine ecosystem. This method argues in favor of expert judgment and qualitative assessment as a decision support tool to the integrative management of estuaries. Namely it allows communicating environmental risk and proposing mitigation measures to local authorities and population under a holistic perspective as an alternative to narrow single line of evidence approaches, which is mandatory to understand cause and effect relationships in complex areas like estuaries.info:eu-repo/semantics/publishedVersio

Low-Carbon Technologies in the Post-Bali Period: Accelerating their Development and Deployment. CEPS ECP Report No. 4, 4 December 2007

This report analyses the very broad issue of technology development, demonstration and diffusion with a view to identifying the key elements of a complementary global technology track in the post-2012 framework. It identifies a number of immediate and concrete steps that can be taken to provide content and a structure for such a track. The report features three sections dealing with innovation and technology, investment in developing countries and investment and finance, followed by an analysis of the various initiatives being taken on technology both within and outside the United Nations Framework Convention on Climate Change (UNFCCC). A final section presents ideas for the way forward followed by brief concluding remarks

Industry 4.0: The Future of Indo-German Industrial Collaboration

Industry 4.0 can be described as the fourth industrial revolution, a mega- trend that affects every company around the world. It envisions interconnections and collaboration between people, products and machines within and across enterprises. Why does Industry 4.0 make for an excellent platform for industrial collaboration between India and Germany? The answers lie in economic as well as social factors. Both countries have strengths and weakness and strategic collaboration using the principles of Industry 4.0 can help both increase their industrial output, GDP and make optimal use of human resources. As a global heavy weight in manufacturing and machine export, Germany has a leading position in the development and deployment of Industry 4.0 concepts and technology. However, its IT sector, formed by a labor force of 800,000 employees, is not enough. It needs more professionals to reach its full potential. India, on the other hand, is a global leader in IT and business process outsourcing. But its manufacturing industry needs to grow significantly and compete globally. These realities clearly show the need for Industry 4.0-based collaboration between Germany and India. So how does Industry 4.0 work? In a first step, we look at the technical pers- pective – the vertical and horizontal integration of Industry 4.0 principles in enterprises. Vertical integration refers to operations within Smart Factories and horizontal integration to Smart Supply Chains across businesses. In the second step, we look at manufacturing, chemical industry and the IT sector as potential targets for collaboration between the two countries. We use case studies to illustrate the benefits of the deployment of Industry 4.0. Potential collaboration patterns are discussed along different forms of value chains and along companies’ ability to achieve Industry 4.0 status. We analyse the social impact of Industry 4.0 on India and Germany and find that it works very well in the coming years. Germany with its dwindling labor force might be compensated through the automation. This will ensure continued high productivity levels and rise in GDP. India, on the other hand has a burgeoning labor market, with 10 million workers annually entering the job market. Given that the manufacturing sector will be at par with Europe in efficiency and costs by 2023, pressure on India’s labor force will increase even more. Even its robust IT sector will suffer fewer hires because of increased automation. Rapid development of technologies – for the Internet of Things (IoT) or for connectivity like Low-Power WAN – makes skilling and reskilling of the labor force critical for augmenting smart manufacturing. India and Germany have been collaborating at three levels relevant to Industry 4.0 – industry, government and academics. How can these be taken forward? The two countries have a long history of trade. The Indo-German Chamber of Commerce (IGCC) is the largest such chamber in India and the largest German chamber worldwide. VDMA (Verband Deutscher Maschinen- und Anlagenbau, Mechanical Engineering Industry Association), the largest industry association in Europe, maintains offices in India. Indian key players in IT, in turn, have subsidia- ries in Germany and cooperate with German companies in the area of Industry 4.0. Collaboration is also supported on governmental level. As government initiatives go, India has launched the “Make in India” initiative and the “Make in India Mittelstand! (MIIM)” programme as a part of it. The Indian Government is also supporting “smart manufacturing” initiatives in a major way. Centers of Excellence driven by the industry and academic bodies are being set up. Germany and India have a long tradition of research collaboration as well. Germany is the second scientific collaborator of India and Indian students form the third largest group of foreign students in Germany. German institutions like the German Academic Exchange Service (DAAD) or the German House for Research and Innovation (DWIH) are working to strengthen ties between the scientific communities of the two countries, and between their academia and industry. What prevents Industry 4.0 from becoming a more widely used technology? Recent surveys in Germany and India show that awareness about Industry 4.0 is still low, especially among small and medium manufacturing enterprises. IT companies, on the other hand, are better prepared. There is a broad demand for support, regarding customtailored solutions, information on case studies and the willingness to participate in Industry 4.0 pilot projects and to engage in its platform and networking activities. We also found similar responses at workshops conducted with Industry 4.0 stakehold- ers in June 2017 in Bangalore and Pune and in an online survey. What can be done to change this? Both countries should strengthen their efforts to create awareness for Industry 4.0, especially among small and medium enterprises. Germany should also put more emphasis on making their Industry 4.0 technology known to the Indian market. India’s IT giants, on the other hand, should make their Industry 4.0 offers more visible to the German market. The governments should support the establishing of joint Industry 4.0 collaboration platforms, centers of excellence and incubators to ease the dissemination of knowledge and technology. On academic level, joint research programs and exchange programs should be set up to foster the skilling of labor force in the deployment of Industry 4.0 methods and technologies