28,426 research outputs found

    Technology Trends in ICT – Towards Data-Driven, Farmer-Centered and Knowledge-Based Hybrid Cloud Architectures for Smart Farming

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    Over the past four decades, advances in Information and Communication Technology (ICT) have resulted in unprecedented opportunity and innovation for improving farming outcomes. Ongoing innovations such as mobile, social media, agricultural drones, Internet of Things (IoT), Big Data, and cloud computing present new challenges and opportunities for agribusinesses to redefine and rethink the role of ICT towards achieving better farming outcomes. With recent advances in infrastructure, data (collection, storage and retrieval), and a better understanding of all aspects of the food chain, new challenges and opportunities are presented. Unstructured data is now being generated real time, in large volumes, at high speed and unknown quality that results in challenges to current approaches for decision making, and require a focus on analytics. These new sources of data create the opportunity to inform and drive a change in decision making from one that is highly intuitive to one that is data driven and processed in real-time. This paper highlights recent trends in ICT and introduces a hybrid cloud architecture for smart farming. The proposed architecture emphasizes data-driven, farmer-centered, and knowledge-based decision tools through service integration, aggregation and interoperation. As a customized solution for farmers, the proposed architecture contains components of 1) data integration of on-farm sensors and data from public sources, 2) farm management modules, 3) knowledge-based software solutions from different providers, 4) service integration, aggregation and interoperation, and 5) a customized dashboard focused on usefulness and usability. This cloud-based solution allows the integration of businesses services, things, and technology from any channel and can be used anywhere. At this time, hybrid cloud environments have shown promise to integrate these different services and provide smart farming solutions to both big and smallholder farmers. 

    Enforcing reputation constraints on business process workflows

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    The problem of trust in determining the flow of execution of business processes has been in the centre of research interst in the last decade as business processes become a de facto model of Internet-based commerce, particularly with the increasing popularity in Cloud computing. One of the main mea-sures of trust is reputation, where the quality of services as provided to their clients can be used as the main factor in calculating service and service provider reputation values. The work presented here contributes to the solving of this problem by defining a model for the calculation of service reputa-tion levels in a BPEL-based business workflow. These levels of reputation are then used to control the execution of the workflow based on service-level agreement constraints provided by the users of the workflow. The main contribution of the paper is to first present a formal meaning for BPEL processes, which is constrained by reputation requirements from the users, and then we demonstrate that these requirements can be enforced using a reference architecture with a case scenario from the domain of distributed map processing. Finally, the paper discusses the possible threats that can be launched on such an architecture

    A survey of communication protocols for internet of things and related challenges of fog and cloud computing integration

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    The fast increment in the number of IoT (Internet of Things) devices is accelerating the research on new solutions to make cloud services scalable. In this context, the novel concept of fog computing as well as the combined fog-to-cloud computing paradigm is becoming essential to decentralize the cloud, while bringing the services closer to the end-system. This article surveys e application layer communication protocols to fulfill the IoT communication requirements, and their potential for implementation in fog- and cloud-based IoT systems. To this end, the article first briefly presents potential protocol candidates, including request-reply and publish-subscribe protocols. After that, the article surveys these protocols based on their main characteristics, as well as the main performance issues, including latency, energy consumption, and network throughput. These findings are thereafter used to place the protocols in each segment of the system (IoT, fog, cloud), and thus opens up the discussion on their choice, interoperability, and wider system integration. The survey is expected to be useful to system architects and protocol designers when choosing the communication protocols in an integrated IoT-to-fog-to-cloud system architecture.Peer ReviewedPostprint (author's final draft

    Support Service for Reciprocal Computational Resource Sharing in Wireless Community Networks

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    In community networks, individuals and local organizations from a geographic area team up to create and run a community-owned IP network to satisfy the community's demand for ICT, such as facilitating Internet access and providing services of local interest. Most current community networks use wireless links for the node interconnection, applying off-the-shelf wireless equipment. While IP connectivity over the shared network infrastructure is successfully achieved, the deployment of applications in community networks is surprisingly low. To address the solution of this problem, we propose in this paper a service to incentivize the contribution of computing and storage as cloud resources to community networks, in order to stimulate the deployment of services and applications. Our final goal is the vision that in the long term, the users of community networks will not need to consume applications from the Internet, but find them within the wireless community network

    Smart Computing and Sensing Technologies for Animal Welfare: A Systematic Review

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    Animals play a profoundly important and intricate role in our lives today. Dogs have been human companions for thousands of years, but they now work closely with us to assist the disabled, and in combat and search and rescue situations. Farm animals are a critical part of the global food supply chain, and there is increasing consumer interest in organically fed and humanely raised livestock, and how it impacts our health and environmental footprint. Wild animals are threatened with extinction by human induced factors, and shrinking and compromised habitat. This review sets the goal to systematically survey the existing literature in smart computing and sensing technologies for domestic, farm and wild animal welfare. We use the notion of \emph{animal welfare} in broad terms, to review the technologies for assessing whether animals are healthy, free of pain and suffering, and also positively stimulated in their environment. Also the notion of \emph{smart computing and sensing} is used in broad terms, to refer to computing and sensing systems that are not isolated but interconnected with communication networks, and capable of remote data collection, processing, exchange and analysis. We review smart technologies for domestic animals, indoor and outdoor animal farming, as well as animals in the wild and zoos. The findings of this review are expected to motivate future research and contribute to data, information and communication management as well as policy for animal welfare

    Real-time predictive maintenance for wind turbines using Big Data frameworks

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    This work presents the evolution of a solution for predictive maintenance to a Big Data environment. The proposed adaptation aims for predicting failures on wind turbines using a data-driven solution deployed in the cloud and which is composed by three main modules. (i) A predictive model generator which generates predictive models for each monitored wind turbine by means of Random Forest algorithm. (ii) A monitoring agent that makes predictions every 10 minutes about failures in wind turbines during the next hour. Finally, (iii) a dashboard where given predictions can be visualized. To implement the solution Apache Spark, Apache Kafka, Apache Mesos and HDFS have been used. Therefore, we have improved the previous work in terms of data process speed, scalability and automation. In addition, we have provided fault-tolerant functionality with a centralized access point from where the status of all the wind turbines of a company localized all over the world can be monitored, reducing O&M costs
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