271 research outputs found

    Smart Greenhouse Design for Strawberry Cultivation in Pandanrejo, Batu City

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    Batu City, which is famous as a tourist city, is not only an urban area. Most of the Batu city area is a rural area, especially the northern area which is included in the Bumiaji sub-district. As a tourist area, Batu City has a large enough economic potential to improve the welfare of its people. Most of the people of Batu city who live in rural areas are fruit and vegetable farmers. Pandanrejo village in Bumiaji sub-district is an example of a strawberry-producing village in Batu city. Various problems are faced by strawberry farmers in Pandanrejo village. One of them is related to the uncertain weather conditions in their village. The ITS Physics department team provides solutions related to these weather conditions with an innovative climate conditioning technology that can be applied in agriculture. This technology is a smart greenhouse in which there is control of environmental conditions for strawberry plants. With the application of smart greenhouse technology, it is expected to increase the productivity of strawberries and the welfare of the farming community of Pandanrejo village, Batu city

    LITERATURE REVIEW IOT SOFTWARE ARCHITECTURE ON AGRICULTURE

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    Context – Internet of Things (IoT) interrelates computing devices, machines, animals, or people and things that use the power of internet usage to utilize data to be much more usable. Food is one of the mandatory human needs to survive, and most of it is produced by agriculture. Using IoT in agriculture needs appropriate software architecture that plays a prominent role in optimizing the gain. Objective and Method – Implementing a solution in a specific field requires a particular condition that belongs to it. The objectives of this research study are to classify the state of the art IoT solution in the software architecture domain perspective. We have used the Evidence- Based Software Engineering (EBSE) and have 24 selected existing studies related to software architecture and IoT solutions to map to the software architecture needed on IoT solutions in agriculture. Result and Implications – The results of this study are the classification of various IoT software architecture solutions in agriculture. The highlighted field, especially in the areas of cloud, big data, integration, and artificial intelligence/machine learning. We mapped the agriculture taxonomy classification with IoT software architecture. For future work, we recommend enhancing the classification and mapping field to the utilization of drones in agriculture since drones can reach a vast area that is very fit for fertilizing, spraying, or even capturing crop images with live cameras to identify leaf disease

    Artificial Intelligence: The Future of Sustainable Agriculture? A Research Agenda

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    Global warming and the increasing food demand are problems of the current generation and require a change towards sustainable agriculture. In recent years, research in the field of artificial intelligence has made considerable progress. Thus, the use of artificial intelligence in agriculture can be a promising solution to ensure sufficient food supply on a global scale. To investigate the state-of-the-art in the use of artificial intelligence-based systems in agriculture, we provide a structured literature review. We show that research has been done in the field of irrigation and plant growth. In this regard, camera systems often provide images as training/input data for artificial intelligence-based systems. Finally, we provide a research agenda to pave the way for further research on the use of artificial intelligence in sustainable agriculture

    Ensuring Agricultural Sustainability through Remote Sensing in the Era of Agriculture 5.0

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    This work was supported by the projects: "VIRTUOUS" funded by the European Union's Horizon 2020 Project H2020-MSCA-RISE-2019. Ref. 872181, "SUSTAINABLE" funded by the European Union's Horizon 2020 Project H2020-MSCA-RISE-2020. Ref. 101007702 and the "Project of Excellence" from Junta de Andalucia 2020. Ref. P18-H0-4700. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Timely and reliable information about crop management, production, and yield is considered of great utility by stakeholders (e.g., national and international authorities, farmers, commercial units, etc.) to ensure food safety and security. By 2050, according to Food and Agriculture Organization (FAO) estimates, around 70% more production of agricultural products will be needed to fulfil the demands of the world population. Likewise, to meet the Sustainable Development Goals (SDGs), especially the second goal of “zero hunger”, potential technologies like remote sensing (RS) need to be efficiently integrated into agriculture. The application of RS is indispensable today for a highly productive and sustainable agriculture. Therefore, the present study draws a general overview of RS technology with a special focus on the principal platforms of this technology, i.e., satellites and remotely piloted aircrafts (RPAs), and the sensors used, in relation to the 5th industrial revolution. Nevertheless, since 1957, RS technology has found applications, through the use of satellite imagery, in agriculture, which was later enriched by the incorporation of remotely piloted aircrafts (RPAs), which is further pushing the boundaries of proficiency through the upgrading of sensors capable of higher spectral, spatial, and temporal resolutions. More prominently, wireless sensor technologies (WST) have streamlined real time information acquisition and programming for respective measures. Improved algorithms and sensors can, not only add significant value to crop data acquisition, but can also devise simulations on yield, harvesting and irrigation periods, metrological data, etc., by making use of cloud computing. The RS technology generates huge sets of data that necessitate the incorporation of artificial intelligence (AI) and big data to extract useful products, thereby augmenting the adeptness and efficiency of agriculture to ensure its sustainability. These technologies have made the orientation of current research towards the estimation of plant physiological traits rather than the structural parameters possible. Futuristic approaches for benefiting from these cutting-edge technologies are discussed in this study. This study can be helpful for researchers, academics, and young students aspiring to play a role in the achievement of sustainable agriculture.European Commission 101007702 872181Junta de Andalucia P18-H0-470

    Review—Machine Learning Techniques in Wireless Sensor Network Based Precision Agriculture

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    The use of sensors and the Internet of Things (IoT) is key to moving the world\u27s agriculture to a more productive and sustainable path. Recent advancements in IoT, Wireless Sensor Networks (WSN), and Information and Communication Technology (ICT) have the potential to address some of the environmental, economic, and technical challenges as well as opportunities in this sector. As the number of interconnected devices continues to grow, this generates more big data with multiple modalities and spatial and temporal variations. Intelligent processing and analysis of this big data are necessary to developing a higher level of knowledge base and insights that results in better decision making, forecasting, and reliable management of sensors. This paper is a comprehensive review of the application of different machine learning algorithms in sensor data analytics within the agricultural ecosystem. It further discusses a case study on an IoT based data-driven smart farm prototype as an integrated food, energy, and water (FEW) system

    Strawberry Cultivation Techniques

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    Among the berries, strawberries are the most commercially produced and consumed and their production and consumption are increasing in the world due to their enthusiastic aroma, taste, and biochemical properties. Strawberry is belonging to the genus Fragaria, from the family Rosaceae. It is indicated that the homeland of the strawberry is South America (Chile). It is well-known that people living in Asia, Europe, and America commonly use the wild F. vesca. In other regions such as Japan, North China and Manchuria, Europe-Siberia, and America there are different ecogeographic zones where alternative species are clustered. Despite its origins in the Pacific Northwest region of North America, F. ananassa is now grown all over the world. Strawberry is one of the most widespread berry species grown in almost every country including high altitudes of tropical regions, and subtropical and temperate areas. In this chapter, we aimed to offer new perspectives on the future of strawberry cultivation techniques by analyzing recent academic studies on strawberry production

    Agriculture 4.0: A systematic literature review on the paradigm, technologies and benefits

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    Demographics will increase the demand for food and reduce the availability of labour in many countries all over the world. Moreover, scarcity of natural resources, climate change and food waste these are issues that are strongly impacting the agricultural sector and undermining sus-tainability. Digitalisation is expected to be a driving force in tackling these problems that are characterising agriculture. In particular, the adoption of digital technologies to support processes in the primary sector goes by the name of Agriculture 4.0. Although the number of contributions related to these issues is constantly growing, several areas are still unexplored or not fully addressed. This paper addresses the adoption of digital technologies and investigates the appli-cation domain of these technologies, presenting a systematic review of the literature on this subject. Moreover, this research shed light on the technologies adopted and related benefits. Hence, the research has turned its attention to the description of the main pillars, such as the categorisation of its main application domains and enabling technologies. The results of the research show that the different technologies applied in the various fields of application provide benefits both in terms of efficiency (cost reduction, farm productivity) and reduced environ-mental impact and increased sustainability

    Machine learning for detection and prediction of crop diseases and pests: A comprehensive survey

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    Considering the population growth rate of recent years, a doubling of the current worldwide crop productivity is expected to be needed by 2050. Pests and diseases are a major obstacle to achieving this productivity outcome. Therefore, it is very important to develop efficient methods for the automatic detection, identification, and prediction of pests and diseases in agricultural crops. To perform such automation, Machine Learning (ML) techniques can be used to derive knowledge and relationships from the data that is being worked on. This paper presents a literature review on ML techniques used in the agricultural sector, focusing on the tasks of classification, detection, and prediction of diseases and pests, with an emphasis on tomato crops. This survey aims to contribute to the development of smart farming and precision agriculture by promoting the development of techniques that will allow farmers to decrease the use of pesticides and chemicals while preserving and improving their crop quality and production.info:eu-repo/semantics/publishedVersio

    Internet of Things Applications in Precision Agriculture: A Review

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    The goal of this paper is to review the implementation of an Internet of Things (IoT)-based system in the precision agriculture sector. Each year, farmers suffer enormous losses as a result of insect infestations and a lack of equipment to manage the farm effectively. The selected article summarises the recommended systematic equipment and approach for implementing an IoT in smart farming. This review's purpose is to identify and discuss the significant devices, cloud platforms, communication protocols, and data processing methodologies. This review highlights an updated technology for agricultural smart management by revising every area, such as crop field data and application utilization. By customizing their technology spending decisions, agriculture stakeholders can better protect the environment and increase food production in a way that meets future global demand. Last but not least, the contribution of this research is that the use of IoT in the agricultural sector helps to improve sensing and monitoring of production, including farm resource usage, animal behavior, crop growth, and food processing. Also, it provides a better understanding of the individual agricultural circumstances, such as environmental and weather conditions, the growth of weeds, pests, and diseases
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