195 research outputs found

    An assessment of stingless beehive climate impact using multivariate recurrent neural networks

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    A healthy bee colony depends on various elements, including a stable habitat, a sufficient source of food, and favorable weather. This paper aims to assess the stingless beehive climate data and examine the precise short-term forecast model for hive weight output. The dataset was extracted from a single hive, for approximately 36-hours, at every seven seconds time stamp. The result represents the correlation analysis between all variables. The evaluation of root-mean-square error (RMSE), as well as the RMSE performance from various types of topologies, are tested on four different forecasting window sizes. The proposed forecast model considers seven of input vectors such as hive weight, an inside temperature, inside humidity, outside temperature, outside humidity, the dewpoint, and bee count. The various network architecture examined for minimal RMSE are long short-term memory (LSTM) and gated recurrent units (GRU). The LSTM1X50 topology was found to be the best fit while analyzing several forecasting windows sizes for the beehive weight forecast. The results obtained indicate a significant unusual symptom occurring in the stingless bee colonies, which allow beekeepers to make decisions with the main objective of improving the colony’s health and propagation

    Supporting metropolitan Venice coastline climate adaptation. A multi-vulnerability and exposure assessment approach

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    Urban planning for adaptation to climate change privileges the construction of cognitive frameworks developed through the use of new spatial technologies and open-source databases. The significant and most highly innovative aspect concerns how resilience to CC under conditions of vulnerability and risk is defined, monitored and assessed. Based on these premises, this paper aims to explore a new methodology of climate vulnerability, exposure and risk analysis through multicriteria assessment techniques by activating a case study in the coastal municipality of Jesolo (Italy). Taking into consideration three main weather-climate impacts (Urban Flooding, Coastal Flooding and Urban Heat Island) the methodology searches for the best geo-referenced data that can best describe the recognizing impact of the cumulative impact condition through testing a GIS-based multi-attribute exploratory procedure. Intersectoral and multilevel vulnerability conditions at different spatial scales are configured. The analysis methodology continues using open source data (from Open Street Map) to construct local exposure information layers. Exposure combined with spatial vulnerability conditions allows the generation of multi-hazard mapping. Experimentation with multi-hazard climate-oriented spatial assessment can guide planning and public decision-making in new policy domains and target mitigation and adaptation actions in land planning, management and regulation practices. Finally, the proposed methodology can activate stakeholder engagement processes within municipalities to discuss the actual perceived risk and begin a collaborative journey with citizens to identify best practices and solutions to adopt in the areas indicated by the risk mapping

    Ecosystem services, sustainable rural development and protected áreas

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    Enhancing social and economic development while preserving nature is one of the major challenges for humankind in the current century. The Millennium Ecosystem Assessment showed an alarming degradation of ecosystems and exacerbated poverty for many groups of people across the world due to unprecedented changes in ecosystems caused by human activities in the 20th century. Sustainable Rural Development is key to maintaining active local communities in rural and semi-natural areas, avoiding depopulation, and preserving high-ecological-value sites, including protected areas. Establishing protected areas is the most common strategy to preserve biodiversity around the world with the advantage of promoting the supply of ecosystem services. However, depending how it affects economic opportunities and the access to natural resources, it can either attract or repel human settlements. The convergence of development and conservation requires decision-making processes capable of aligning the needs and expectations of rural communities and the goals of biodiversity conservation. The articles compiled in this Special Issue (nine research papers and two review papers) make important contributions to this challenge from different approaches, disciplines and regions in the world.info:eu-repo/semantics/publishedVersio

    Low-Cost Inventions and Patents

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    Inventions have led to the technological advances of mankind. There are inventions of all kinds, some of which have lasted hundreds of years or even longer. Low-cost technologies are expected to be easy to build, have little or no energy consumption, and be easy to maintain and operate. The use of sustainable technologies is essential in order to move towards a greater global coverage of technology, and therefore to improve human quality of life. Low-cost products always respond to a specific need, even if no in-depth analysis of the situation or possible solutions has been carried out. It is a consensus in all industrialized countries that patents have a decisive influence on the organization of the economy, as they are a key element in promoting technological innovation. Patents must aim to promote the technological development of countries, starting from their industrial situations

    CERNAS: Current Evolution and Research Novelty in Agricultural Sustainability

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    Climate changes pose overwhelming impacts on primary production and, consequently, on agricultural and animal farming. Additionally, at present, agriculture still depends strongly on fossil fuels both for energy and production factors ,such as synthetized inorganic fertilizers and harmful chemicals such as pesticides. The need to feed the growing world population poses many challenges. The need to reduce environmental impacts to a minimum, maintain healthy ecosystems, and improve soil microbiota are central to ensuring a promising future for coming generations. Livestock production under cover crop systems helps to alleviate compaction so that oxygen and water can sufficiently flow in the soil, add organic matter, and help hold soil in place, reducing crusting and protecting against erosion. The use of organic plant production practices allied to the control of substances used in agriculture also decisively contributes to alleviating the pressure on ecosystems. Some of the goals of this new decade are to use enhanced sustainable production methodologies to improve the input/output ratios of primary production, reduce environmental impacts, and rely on new innovative technologies. This reprint addresses original studies and reviews focused on the current evolution and research novelty in agricultural sustainability. New developments are discussed on issues related to quality of soil, natural fertilizers, or the sustainable use of land and water. Also, crop protection techniques are pivotal for sustainable food production under the challenges of the Sustainable Development Goals of the United Nations, allied to innovative weed control methodologies as a way to reduce the utilization of pesticides. The role of precision and smart agriculture is becoming more pertinent as communication technologies improve at a rapid rate. Waste management, reuse of agro-industrial residues, extension of shelf life, and use of new technologies are ways to reduce food waste, all contributing to higher sustainability in food supply chains, leading to a more rational use of natural resources. The unquestionable role of bees as pollinators and contributors to biodiversity is adjacent to characterizing beekeeping activities, which in turn contributes, together with the valorization of endemic varieties of plant foods, to the development of local communities. Finally, the short circuits and local food markets have a decisive role in the preservation and enhancement of rural economies.info:eu-repo/semantics/publishedVersio

    CERNAS – Current Evolution and Research Novelty in Agricultural Sustainability

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    This book addresses original studies and reviews focused on the current evolution and research novelty in agricultural sustainability. New developments are discussed on issues related with quality of soil, natural fertilizers or the sustainable use of land and water. Also crop protection techniques are pivotal for the sustainable food production under the challenges of the Sustainable Development Goals of the United Nations, allied to innovative weed control methodologies, as a way to reduce the utilization of pesticides. The role of precision and smart agriculture is becoming more pertinent as the communication technologies improve at a high rate. Waste management, reuse of agro industrial residues, extension of shelf life and use of new technologies are ways to reduce food waste, all contributing to a higher sustainability of the food supply chains, leading to a more rational use of natural resources. The unquestionable role of bees as pollinators and contributors for biodiversity is subjacent to the work of characterization of beekeeping activities, which in turn contribute, together with the valorization of endemic varieties of plant foods, for the development of local communities. Finally, the short circuits and local food markets have a decisive role in the preservation and enhancement of rural economies.info:eu-repo/semantics/publishedVersio

    Pertanika Journal of Science & Technology

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    Bee Hive Monitoring System - Solutions for the automated health monitoring

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    Cerca de um terço da produção global de alimentos depende da polinização das abelhas, tornando-as vitais para a economia mundial. No entanto, existem diversas ameaças à sobrevivência das espécies de abelhas, tais como incêndios florestais, stress humano induzido, subnutrição, poluição, perda de biodiversidade, agricultura intensiva e predadores como as vespas asiáticas. Destes problemas, pode-se observar um aumento da necessidade de soluções automatizadas que possam auxiliar na monitorização remota de colmeias de abelhas. O objetivo desta tese é desenvolver soluções baseadas em Aprendizagem Automática para problemas que podem ser identificados na apicultura, usando técnicas e conceitos de Deep Learning, Visão Computacional e Processamento de Sinal. Este documento descreve o trabalho da tese de mestrado, motivado pelo problema acima exposto, incluindo a revisão de literatura, análise de valor, design, planeamento de testes e validação e o desenvolvimento e estudo computacional das soluções. Concretamente, o trabalho desta tese de mestrado consistiu no desenvolvimento de soluções para três problemas – classificação da saúde de abelhas a partir de imagens e a partir de áudio, e deteção de abelhas e vespas asiáticas. Os resultados obtidos para a classificação da saúde das abelhas a partir de imagens foram significativamente satisfatórios, excedendo os que foram obtidos pela metodologia definida no trabalho base utilizado para a tarefa, que foi encontrado durante a revisão da literatura. No caso da classificação da saúde das abelhas a partir de áudio e da deteção de abelhas e vespas asiáticas, os resultados obtidos foram modestos e demonstram potencial aplicabilidade das respetivas metodologias desenvolvidas nos problemas-alvo. Pretende-se que as partes interessadas desta tese consigam obter informações, metodologias e perceções adequadas sobre o desenvolvimento de soluções de IA que possam ser integradas num sistema de monitorização da saúde de abelhas, incluindo custos e desafios inerentes à implementação das soluções. O trabalho futuro desta dissertação de mestrado consiste em melhorar os resultados dos modelos de classificação da saúde das abelhas a partir de áudio e de deteção de objetos, incluindo a publicação de artigos para obter validação pela comunidade científica.Up to one third of the global food production depends on the pollination of honey bees, making them vital for the world economy. However, between forest fires, human-induced stress, poor nutrition, pollution, biodiversity loss, intensive agriculture, and predators such as Asian Hornets, there are plenty of threats to the honey bee species’ survival. From these problems, a rise of the need for automated solutions that can aid with remote monitoring of bee hives can be observed. The goal of this thesis is to develop Machine Learning based solutions to problems that can be identified in beekeeping and apiculture, using Deep Learning, Computer Vision and Signal Processing techniques and concepts. The current document describes master thesis’ work, motivated from the above problem statement, including the literature review, value analysis, design, testing and validation planning and the development and computational study of the solutions. Specifically, this master thesis’ work consisted in developing solutions to three problems – bee health classification through images and audio, and bee and Asian wasp detection. Results obtained for the bee health classification through images were significantly satisfactory, exceeding those reported by the baseline work found during literature review. On the case of bee health classification through audio and bee and Asian wasp detection, these obtained results were modest and showcase potential applicability of the respective developed methodologies in the target problems. It is expected that stakeholders of this thesis obtain adequate information, methodologies and insights into the development of AI solutions that can be integrated in a bee health monitoring system, including inherent costs and challenges that arise with the implementation of the solutions. Future work of this master thesis consists in improving the results of the bee health classification through audio and the object detection models, including publishing of papers to seek validation by the scientific community

    Environmental Information Systems and Community-Based Resource Management in Ghana: An Investigation of Institutional Policy and Implementation in Context

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    This study employed a case-study approach and cross-case analysis to investigate the impact of Environmental Information Systems (EIS) and Local Knowledge Systems (LKS) on agro-forestry management and biodiversity conservation. Questionnaire-based interviews with service providers, resource managers and focus group discussions with farmers associated with the United Nations Capacity 21, the Netherlands Tropenbos International (TBI) and the United Nations Project on People Land Management and Conservation (UNPLEC), projects yielded in-depth information on agro-forestry practices in southern Ghana. The findings of the survey revealed that computer-based information systems have been used to identify areas of resource degradation. This has served as a sanitization tool to organize and intensify tree-planting exercises and agroforestry management activities in the affected areas. Evaluation of individual cases and cross-case analysis of EIS projects in Ghana showed parallels and divergences in the modus operandi of EIS implementation at national and district levels. The Capacity 21 project initiated the District Environmental Resource Information System (DERIS). The project procured datasets (eg. satellite images, software, computers and printers) in 8 pilot districts including Sekyere West and Assin Fosu Districts and offered training and skill development programmes under the auspices of the Centre for Environmental Remote Sensing and Geographic Information Services (CERSGIS) to equip focal district planning officers to use tools and datasets to analyze the state of the environment and the extent of resource degradation as well as other development-related activities. This fostered cooperation between the national coordinator of the project, district planners and local farmers to organize regular tree-planting exercises and workshops on alternative livelihood activities which have helped to lessen pressure on the environment to some extent. This approach exhibits a greater degree of top-down planning and implementation. The field survey revealed that PLEC used computer-based information systems during the earlier stages of the project to demarcate demonstration sites and capture spatio-temporal variations in agro-ecological conditions. However, during the subsequent phases, the PLEC project relied heavily and predominantly on local agro-ecological knowledge from a diverse group of farmers to assess resource conditions, and promoted the use of various traditional and exotic agro-forestry and agro-diversity management techniques in the Manya Krobo and Suhum Kraboa Coaltar Districts. The PLEC approach was more bottom-up in its philosophy and practice by allowing natural and social scientists to learn from farmers, and the scientists in turn offered technical advice which enabled farmers to improve their local farming techniques and maximize their farm productivity, while at the same time enhancing the capacity of the biophysical environment to support conventional and alternative livelihood activities continually. The Tropenbos International (TBI) project exhibits elements of both top-down and bottom-up implementation approaches. It recognizes the significant role of tailor-made information (computer-based systems and socio-economic studies mainly from the Forest Services Commission and the University of Ghana, respectively) and skill in forest management. The TBI GORTMAN project streamlined the capacity for information collection in the Goaso and Offinso districts. The findings revealed that farmers associated with the three projects apply various knowledge systems and techniques in agroforestry management. These include, mixed cultivation of domestic, economic and medicinal trees as well as food crops. Reasons such as windbreak, construction materials, medicine, food, fuelwood and nutrient enhancement were cited by farmers for practicing agroforestry. Common food crops found on farms include cocoyam, okro, maize, plantain and yams, among others. These crops are the mainstay of family food and income sources. Other livelihood activities include beekeeping, snail rearing and grasscutter raising and livestock breeding. The diversities of agroforestry practices have engendered decades of farm management practices and resource conservation measures. Another challenge of agroforestry management which is common to all the three projects is that farmers are victims of indiscriminate felling of trees on their farms by timber companies which destroys their crops. Farmers repeatedly cited logistical (tools, seedlings etc) challenges and financial constraints as factors that hamper effective application of knowledge systems in agroforestry management. This is a dominant problem that PLEC and TBI farmers face. Capacity 21 farmers benefited initially from logistical supplies but it was short-lived. In view of these problems, the study recommended measures for improving environmental information systems and local knowledge systems applications in agroforestry management and agrodiversity conservation in southern Ghana
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