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Prof. Dionysis Bochtis
Centre for Research and Technology - Hellas (CERTH)

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0 Agricultural Engineering
0 Operations Management
0 Optimization
0 Planning
0 Robotics

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Journal article
Published: 18 August 2021 in Applied Sciences
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Traceability, namely the ability to access information about a product and its movement across all stages of the supply chain, has been emerged as a key criterion of a product’s quality and safety. Managing fresh products, such as fruits and vegetables, is a particularly complicated task, since they are perishable with short shelf lives and are vulnerable to environmental conditions. This makes traceability of fresh produce very significant. The present study provides a brief overview of the relative literature on fresh produce traceability systems. It was concluded that the commercially available traceability systems usually neither cover the entire length of the supply chain nor rely on open and transparent interoperability standards. Therefore, a user-friendly open access traceability system is proposed for the development of an integrated solution for traceability and agro-logistics of fresh products, focusing on interoperability and data sharing. Various Internet of Things technologies are incorporated and connected to the web, while an android-based platform enables the monitoring of the quality of fruits and vegetables throughout the whole agri-food supply chain, starting from the field level to the consumer and back to the field. The applicability of the system, named AgroTRACE, is further extended to waste management, which constitutes an important aspect of a circular economy.

ACS Style

Aristotelis C. Tagarakis; Lefteris Benos; Dimitrios Kateris; Nikolaos Tsotsolas; Dionysis Bochtis. Bridging the Gaps in Traceability Systems for Fresh Produce Supply Chains: Overview and Development of an Integrated IoT-Based System. Applied Sciences 2021, 11, 7596 .

AMA Style

Aristotelis C. Tagarakis, Lefteris Benos, Dimitrios Kateris, Nikolaos Tsotsolas, Dionysis Bochtis. Bridging the Gaps in Traceability Systems for Fresh Produce Supply Chains: Overview and Development of an Integrated IoT-Based System. Applied Sciences. 2021; 11 (16):7596.

Chicago/Turabian Style

Aristotelis C. Tagarakis; Lefteris Benos; Dimitrios Kateris; Nikolaos Tsotsolas; Dionysis Bochtis. 2021. "Bridging the Gaps in Traceability Systems for Fresh Produce Supply Chains: Overview and Development of an Integrated IoT-Based System." Applied Sciences 11, no. 16: 7596.

Journal article
Published: 24 June 2021 in Applied Sciences
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Wireless sensor networks (WSNs) can be reliable tools in agricultural management. In this work, a low cost, low power consumption, and simple wireless sensing system dedicated for agricultural environments is presented. The system is applicable to small to medium sized fields, located anywhere with cellular network coverage, even in isolated rural areas. The novelty of the developed system lies in the fact that it uses a dummy device as Coordinator which through simple but advanced programming can receive, process, and send data packets from all End-nodes to the cloud via a 4G cellular network. Furthermore, it is energy independent, using solar energy harvesting panels, making it feasible to operate in remote, isolated fields. A star topology was followed for the sake of simplification, low energy demands and increased network reliability. The developed system was tested and evaluated in laboratory and real field environment with satisfactory operation in terms of independence, and operational reliability concerning packet losses, communication range (>250 m covering fields up to 36 ha), energy autonomy, and uninterrupted operation. The network can support up to seven nodes in a 30 min data acquisition cycle. These results confirmed the potential of this system to serve as a viable option for monitoring environmental, soil, and crop parameters.

ACS Style

Aristotelis Tagarakis; Dimitrios Kateris; Remigio Berruto; Dionysis Bochtis. Low-Cost Wireless Sensing System for Precision Agriculture Applications in Orchards. Applied Sciences 2021, 11, 5858 .

AMA Style

Aristotelis Tagarakis, Dimitrios Kateris, Remigio Berruto, Dionysis Bochtis. Low-Cost Wireless Sensing System for Precision Agriculture Applications in Orchards. Applied Sciences. 2021; 11 (13):5858.

Chicago/Turabian Style

Aristotelis Tagarakis; Dimitrios Kateris; Remigio Berruto; Dionysis Bochtis. 2021. "Low-Cost Wireless Sensing System for Precision Agriculture Applications in Orchards." Applied Sciences 11, no. 13: 5858.

Journal article
Published: 31 May 2021 in Sensors
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This study aimed to propose an approach for orchard trees segmentation using aerial images based on a deep learning convolutional neural network variant, namely the U-net network. The purpose was the automated detection and localization of the canopy of orchard trees under various conditions (i.e., different seasons, different tree ages, different levels of weed coverage). The implemented dataset was composed of images from three different walnut orchards. The achieved variability of the dataset resulted in obtaining images that fell under seven different use cases. The best-trained model achieved 91%, 90%, and 87% accuracy for training, validation, and testing, respectively. The trained model was also tested on never-before-seen orthomosaic images or orchards based on two methods (oversampling and undersampling) in order to tackle issues with out-of-the-field boundary transparent pixels from the image. Even though the training dataset did not contain orthomosaic images, it achieved performance levels that reached up to 99%, demonstrating the robustness of the proposed approach.

ACS Style

Athanasios Anagnostis; Aristotelis Tagarakis; Dimitrios Kateris; Vasileios Moysiadis; Claus Sørensen; Simon Pearson; Dionysis Bochtis. Orchard Mapping with Deep Learning Semantic Segmentation. Sensors 2021, 21, 3813 .

AMA Style

Athanasios Anagnostis, Aristotelis Tagarakis, Dimitrios Kateris, Vasileios Moysiadis, Claus Sørensen, Simon Pearson, Dionysis Bochtis. Orchard Mapping with Deep Learning Semantic Segmentation. Sensors. 2021; 21 (11):3813.

Chicago/Turabian Style

Athanasios Anagnostis; Aristotelis Tagarakis; Dimitrios Kateris; Vasileios Moysiadis; Claus Sørensen; Simon Pearson; Dionysis Bochtis. 2021. "Orchard Mapping with Deep Learning Semantic Segmentation." Sensors 21, no. 11: 3813.

Review
Published: 28 May 2021 in Sensors
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The digital transformation of agriculture has evolved various aspects of management into artificial intelligent systems for the sake of making value from the ever-increasing data originated from numerous sources. A subset of artificial intelligence, namely machine learning, has a considerable potential to handle numerous challenges in the establishment of knowledge-based farming systems. The present study aims at shedding light on machine learning in agriculture by thoroughly reviewing the recent scholarly literature based on keywords’ combinations of “machine learning” along with “crop management”, “water management”, “soil management”, and “livestock management”, and in accordance with PRISMA guidelines. Only journal papers were considered eligible that were published within 2018–2020. The results indicated that this topic pertains to different disciplines that favour convergence research at the international level. Furthermore, crop management was observed to be at the centre of attention. A plethora of machine learning algorithms were used, with those belonging to Artificial Neural Networks being more efficient. In addition, maize and wheat as well as cattle and sheep were the most investigated crops and animals, respectively. Finally, a variety of sensors, attached on satellites and unmanned ground and aerial vehicles, have been utilized as a means of getting reliable input data for the data analyses. It is anticipated that this study will constitute a beneficial guide to all stakeholders towards enhancing awareness of the potential advantages of using machine learning in agriculture and contributing to a more systematic research on this topic.

ACS Style

Lefteris Benos; Aristotelis Tagarakis; Georgios Dolias; Remigio Berruto; Dimitrios Kateris; Dionysis Bochtis. Machine Learning in Agriculture: A Comprehensive Updated Review. Sensors 2021, 21, 3758 .

AMA Style

Lefteris Benos, Aristotelis Tagarakis, Georgios Dolias, Remigio Berruto, Dimitrios Kateris, Dionysis Bochtis. Machine Learning in Agriculture: A Comprehensive Updated Review. Sensors. 2021; 21 (11):3758.

Chicago/Turabian Style

Lefteris Benos; Aristotelis Tagarakis; Georgios Dolias; Remigio Berruto; Dimitrios Kateris; Dionysis Bochtis. 2021. "Machine Learning in Agriculture: A Comprehensive Updated Review." Sensors 21, no. 11: 3758.

Journal article
Published: 02 March 2021 in Applied Sciences
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The present study deals with human awareness, which is a very important aspect of human–robot interaction. This feature is particularly essential in agricultural environments, owing to the information-rich setup that they provide. The objective of this investigation was to recognize human activities associated with an envisioned synergistic task. In order to attain this goal, a data collection field experiment was designed that derived data from twenty healthy participants using five wearable sensors (embedded with tri-axial accelerometers, gyroscopes, and magnetometers) attached to them. The above task involved several sub-activities, which were carried out by agricultural workers in real field conditions, concerning load lifting and carrying. Subsequently, the obtained signals from on-body sensors were processed for noise-removal purposes and fed into a Long Short-Term Memory neural network, which is widely used in deep learning for feature recognition in time-dependent data sequences. The proposed methodology demonstrated considerable efficacy in predicting the defined sub-activities with an average accuracy of 85.6%. Moreover, the trained model properly classified the defined sub-activities in a range of 74.1–90.4% for precision and 71.0–96.9% for recall. It can be inferred that the combination of all sensors can achieve the highest accuracy in human activity recognition, as concluded from a comparative analysis for each sensor’s impact on the model’s performance. These results confirm the applicability of the proposed methodology for human awareness purposes in agricultural environments, while the dataset was made publicly available for future research.

ACS Style

Athanasios Anagnostis; Lefteris Benos; Dimitrios Tsaopoulos; Aristotelis Tagarakis; Naoum Tsolakis; Dionysis Bochtis. Human Activity Recognition through Recurrent Neural Networks for Human–Robot Interaction in Agriculture. Applied Sciences 2021, 11, 2188 .

AMA Style

Athanasios Anagnostis, Lefteris Benos, Dimitrios Tsaopoulos, Aristotelis Tagarakis, Naoum Tsolakis, Dionysis Bochtis. Human Activity Recognition through Recurrent Neural Networks for Human–Robot Interaction in Agriculture. Applied Sciences. 2021; 11 (5):2188.

Chicago/Turabian Style

Athanasios Anagnostis; Lefteris Benos; Dimitrios Tsaopoulos; Aristotelis Tagarakis; Naoum Tsolakis; Dionysis Bochtis. 2021. "Human Activity Recognition through Recurrent Neural Networks for Human–Robot Interaction in Agriculture." Applied Sciences 11, no. 5: 2188.

Journal article
Published: 01 January 2021 in Revista Cerrados
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O objetivo deste trabalho é analisar a dinâmica temporal da paisagem e mensurar o estado de conservação ambiental do município de Denise, no Estado de Mato Grosso, na perspectiva de gerar informações que contribuam para o planejamento ambiental. Os mapas de cobertura vegetal e usos da terra foram elaborados a partir de imagens dos satélites Landsat-5, dos anos de 1998 e 2008, e Landsat-8, de 2018. Foram realizados os processos de georreferenciamento, recorte e classificação. A mensuração do estado de conservação ambiental foi realizada mediante a aplicação do Índice de Transformação Antrópica (ITA). No período de análise, foi observado um crescimento das classes agricultura (66,97%), vegetação natural florestal (1,79%) e usos antrópicos (32,40%). Entrementes, houve uma redução nas áreas de pastagem (33,54%), que foram convertidas em agricultura, em especial o cultivo da cana-de-açúcar. As Áreas de Preservação Permanentes (APPs) apresentaram 25,42% em desacordo com a legislação ambiental. O ITA foi classificado como regular. Conclui-se que apesar da municipalidade não apresentar piora no estado de conservação ambiental o aumento no valor da pressão antrópica sobre a paisagem sugere que deve haver uma maior preocupação com as questões ambientais, atentando-se para áreas mais sensíveis como as APPs, que exercem importantes funções ecológicas.

ACS Style

Vitor Alfeu Guedes Moreira Vieira; Alexander Webber Perlandim Ramos; Rafael Cesar Tieppo. Análise temporal da dinâmica da paisagem do município de Denise-Mato Grosso, Brasil. Revista Cerrados 2021, 19, 160 -180.

AMA Style

Vitor Alfeu Guedes Moreira Vieira, Alexander Webber Perlandim Ramos, Rafael Cesar Tieppo. Análise temporal da dinâmica da paisagem do município de Denise-Mato Grosso, Brasil. Revista Cerrados. 2021; 19 (01):160-180.

Chicago/Turabian Style

Vitor Alfeu Guedes Moreira Vieira; Alexander Webber Perlandim Ramos; Rafael Cesar Tieppo. 2021. "Análise temporal da dinâmica da paisagem do município de Denise-Mato Grosso, Brasil." Revista Cerrados 19, no. 01: 160-180.

Review
Published: 30 December 2020 in Energies
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Circular economy is emerging as a regenerative concept that minimizes emissions, relies on renewable energy, and eliminates waste based on the design of closed-loop systems and the reuse of materials and resources. The implementation of circular economy practices in resource-consuming agricultural systems is essential for reducing the environmental ramifications of the currently linear systems. As the renewable segment of circular economy, bioeconomy facilitates the production of renewable biological resources (i.e., biomass) that transform into nutrients, bio-based products, and bioenergy. The use of recycled agro-industrial wastewater in agricultural activities (e.g., irrigation) can further foster the circularity of the bio-based systems. In this context, this paper aims to provide a literature review in the field of circular economy for the agrifood sector to enhance resource efficiency by: (i) minimizing the use of natural resources (e.g., water, energy), (ii) decreasing the use of chemical fertilizers, (iii) utilizing bio-based materials (e.g., agricultural/livestock residues), and (iv) reusing wastewater from agrifood operations. The final objective is to investigate any direct or indirect interactions within the water-energy-nutrients nexus. The derived framework of synergetic circular economy interventions in agriculture can act as a basis for developing circular bio-based business models and creating value-added agrifood products.

ACS Style

Efthymios Rodias; Eirini Aivazidou; Charisios Achillas; Dimitrios Aidonis; Dionysis Bochtis. Water-Energy-Nutrients Synergies in the Agrifood Sector: A Circular Economy Framework. Energies 2020, 14, 159 .

AMA Style

Efthymios Rodias, Eirini Aivazidou, Charisios Achillas, Dimitrios Aidonis, Dionysis Bochtis. Water-Energy-Nutrients Synergies in the Agrifood Sector: A Circular Economy Framework. Energies. 2020; 14 (1):159.

Chicago/Turabian Style

Efthymios Rodias; Eirini Aivazidou; Charisios Achillas; Dimitrios Aidonis; Dionysis Bochtis. 2020. "Water-Energy-Nutrients Synergies in the Agrifood Sector: A Circular Economy Framework." Energies 14, no. 1: 159.

Editorial
Published: 04 December 2020 in Sustainability
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In recent years, bioeconomy strategies have been successfully implemented and widely adopted internationally

ACS Style

Charisios Achillas; Dionysis Bochtis. Toward a Green, Closed-Loop, Circular Bioeconomy: Boosting the Performance Efficiency of Circular Business Models. Sustainability 2020, 12, 10142 .

AMA Style

Charisios Achillas, Dionysis Bochtis. Toward a Green, Closed-Loop, Circular Bioeconomy: Boosting the Performance Efficiency of Circular Business Models. Sustainability. 2020; 12 (23):10142.

Chicago/Turabian Style

Charisios Achillas; Dionysis Bochtis. 2020. "Toward a Green, Closed-Loop, Circular Bioeconomy: Boosting the Performance Efficiency of Circular Business Models." Sustainability 12, no. 23: 10142.

Journal article
Published: 06 October 2020 in Sustainability
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Municipal Solid Waste (MSW) management has been a major problem of modern cities for many years. Thus, the development of optimal waste management strategies has been a priority for the European Commission, especially in the transition toward a circular economy. In this paper, an analysis of different MSW treatment methods that can be effectively implemented in the Region of Central Macedonia (RCM) is provided, and their comparison from an environmental point of view is performed. The assessment is based on real data indicated in the recently updated Greek National Waste Management Plan, whereas the different scenarios developed include landfilling without energy recovery, landfilling with energy recovery, recycling and secondary materials recovery, mechanical-biological treatment, bio-waste composting and anaerobic digestion with energy recovery, and incineration with energy recovery. The obtained results illustrate that efficient waste streams sorting is of vital importance for the effective implementation of an integrated waste management system toward the sustainable management of MSW.

ACS Style

Georgios Banias; Maria Batsioula; Charisios Achillas; Sotiris Patsios; Konstantinos Kontogiannopoulos; Dionysis Bochtis; Nicolas Moussiopoulos. A Life Cycle Analysis Approach for the Evaluation of Municipal Solid Waste Management Practices: The Case Study of the Region of Central Macedonia, Greece. Sustainability 2020, 12, 8221 .

AMA Style

Georgios Banias, Maria Batsioula, Charisios Achillas, Sotiris Patsios, Konstantinos Kontogiannopoulos, Dionysis Bochtis, Nicolas Moussiopoulos. A Life Cycle Analysis Approach for the Evaluation of Municipal Solid Waste Management Practices: The Case Study of the Region of Central Macedonia, Greece. Sustainability. 2020; 12 (19):8221.

Chicago/Turabian Style

Georgios Banias; Maria Batsioula; Charisios Achillas; Sotiris Patsios; Konstantinos Kontogiannopoulos; Dionysis Bochtis; Nicolas Moussiopoulos. 2020. "A Life Cycle Analysis Approach for the Evaluation of Municipal Solid Waste Management Practices: The Case Study of the Region of Central Macedonia, Greece." Sustainability 12, no. 19: 8221.

Journal article
Published: 05 October 2020 in Sustainability
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COVID-19 and the restrictive measures towards containing the spread of its infections have seriously affected the agricultural workforce and jeopardized food security. The present study aims at assessing the COVID-19 pandemic impacts on agricultural labor and suggesting strategies to mitigate them. To this end, after an introduction to the pandemic background, the negative consequences on agriculture and the existing mitigation policies, risks to the agricultural workers were benchmarked across the United States’ Standard Occupational Classification system. The individual tasks associated with each occupation in agricultural production were evaluated on the basis of potential COVID-19 infection risk. As criteria, the most prevalent virus transmission mechanisms were considered, namely the possibility of touching contaminated surfaces and the close proximity of workers. The higher risk occupations within the sector were identified, which facilitates the allocation of worker protection resources to the occupations where they are most needed. In particular, the results demonstrated that 50% of the agricultural workforce and 54% of the workers’ annual income are at moderate to high risk. As a consequence, a series of control measures need to be adopted so as to enhance the resilience and sustainability of the sector as well as protect farmers including physical distancing, hygiene practices, and personal protection equipment.

ACS Style

Dionysis Bochtis; Lefteris Benos; Maria Lampridi; Vasso Marinoudi; Simon Pearson; Claus Sørensen. Agricultural Workforce Crisis in Light of the COVID-19 Pandemic. Sustainability 2020, 12, 8212 .

AMA Style

Dionysis Bochtis, Lefteris Benos, Maria Lampridi, Vasso Marinoudi, Simon Pearson, Claus Sørensen. Agricultural Workforce Crisis in Light of the COVID-19 Pandemic. Sustainability. 2020; 12 (19):8212.

Chicago/Turabian Style

Dionysis Bochtis; Lefteris Benos; Maria Lampridi; Vasso Marinoudi; Simon Pearson; Claus Sørensen. 2020. "Agricultural Workforce Crisis in Light of the COVID-19 Pandemic." Sustainability 12, no. 19: 8212.

Review article
Published: 24 September 2020 in Biosystems Engineering
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An emerging scientific field is the study of safety and ergonomics in the agricultural sector during human-robot interaction. Human-robotic synergetic systems are considered to be the most mature way to circumvent problems appearing due to the complex and unpredictable nature of the agricultural environment, which contrasts with the stable domain found in industrial settings. In promising working ecosystems, the distinctive cognitive human characteristics of perception, decision making and acting can be combined with the strength and repeatable accuracy of robots. However, safety must be guaranteed both in terms of avoiding accidents during unwanted physical contacts and provoking musculoskeletal disorders. The latter is a concise term for describing numerous soft tissues disorders, which have reached epidemic proportions among farmers undermining their quality of life. This investigation, by describing the fundamentals of human-robot interaction from an agriculture-oriented perspective, methodically tries to identify potential hazards that can put human safety at risk. In order to overcome these hazards, approaches for minimising the occurrence of injuries analysed along with methods for safe collaboration. The innovation of this study lies on focusing on ergonomics during agricultural human-robot interactive operations. Thus, through reviewing the basic ergonomic principles and the main risk factors, potential challenges are captured concerning human factors, technologies and policy directions. Ensuring of safety in this kind of systems should have a positive impact in technological, societal and economic aspects. For this purpose, an intensive effort and interdisciplinary collaboration are required to establish a sustainable anthropocentric human-robot interactive ecosystem.

ACS Style

Lefteris Benos; Avital Bechar; Dionysis Bochtis. Safety and ergonomics in human-robot interactive agricultural operations. Biosystems Engineering 2020, 200, 55 -72.

AMA Style

Lefteris Benos, Avital Bechar, Dionysis Bochtis. Safety and ergonomics in human-robot interactive agricultural operations. Biosystems Engineering. 2020; 200 ():55-72.

Chicago/Turabian Style

Lefteris Benos; Avital Bechar; Dionysis Bochtis. 2020. "Safety and ergonomics in human-robot interactive agricultural operations." Biosystems Engineering 200, no. : 55-72.

Journal article
Published: 21 August 2020 in Sustainability
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The assessment of an investment is currently carried out by using mainly financial tools. This work presents a new model for the assessment of the sustainability of an industrial investment and focuses on the development of a holistic framework with the use of indicators. With the use of multi-criteria decision analysis, the framework evaluates a total of eighteen (18) alternative indicators in order to select the optimal bundle to be used for the assessment of future industrial investments. The proposed indicators are selected based on relevant data from the literature, taking into account the principles of prevention, planning and designing. The alternatives are assessed over four (4) criteria, namely environment, society, economy and technology, which are grounded on the principles of sustainable development. Depending on the special characteristics of the programme that is foreseen to fund the potential investments, the decision-maker is provided with a hierarchized set of indicators over which the alternative investments could be optimally assessed in parallel with widely used indicators that strictly assess economic performance. In the present work, twelve (12) different scenarios are examined, incorporating different values in the coefficients of the criteria. For the majority of the scenarios examined (a sensitivity analysis is also provided), the alternative indicator that is assessed with the highest score is “Resource Savings”, followed by “Recycling” and “Research, Innovation, Development”.

ACS Style

Paraskevi Ovezikoglou; Dimitrios Aidonis; Charisios Achillas; Christos Vlachokostas; Dionysis Bochtis. Sustainability Assessment of Investments Based on a Multiple Criteria Methodological Framework. Sustainability 2020, 12, 6805 .

AMA Style

Paraskevi Ovezikoglou, Dimitrios Aidonis, Charisios Achillas, Christos Vlachokostas, Dionysis Bochtis. Sustainability Assessment of Investments Based on a Multiple Criteria Methodological Framework. Sustainability. 2020; 12 (17):6805.

Chicago/Turabian Style

Paraskevi Ovezikoglou; Dimitrios Aidonis; Charisios Achillas; Christos Vlachokostas; Dionysis Bochtis. 2020. "Sustainability Assessment of Investments Based on a Multiple Criteria Methodological Framework." Sustainability 12, no. 17: 6805.

Journal article
Published: 09 August 2020 in Sustainability
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The present research study explores three types of neural network approaches for forecasting natural gas consumption in fifteen cities throughout Greece; a simple perceptron artificial neural network (ANN), a state-of-the-art Long Short-Term Memory (LSTM), and the proposed deep neural network (DNN). In this research paper, a DNN implementation is proposed where variables related to social aspects are introduced as inputs. These qualitative factors along with a deeper, more complex architecture are utilized for improving the forecasting ability of the proposed approach. A comparative analysis is conducted between the proposed DNN, the simple ANN, and the advantageous LSTM, with the results offering a deeper understanding the characteristics of Greek cities and the habitual patterns of their residents. The proposed implementation shows efficacy on forecasting daily values of energy consumption for up to four years. For the evaluation of the proposed approach, a real-life dataset for natural gas prediction was used. A detailed discussion is provided on the performance of the implemented approaches, the ANN and the LSTM, that are characterized as particularly accurate and effective in the literature, and the proposed DNN with the inclusion of the qualitative variables that govern human behavior, which outperforms them.

ACS Style

Athanasios Anagnostis; Elpiniki Papageorgiou; Dionysis Bochtis. Application of Artificial Neural Networks for Natural Gas Consumption Forecasting. Sustainability 2020, 12, 6409 .

AMA Style

Athanasios Anagnostis, Elpiniki Papageorgiou, Dionysis Bochtis. Application of Artificial Neural Networks for Natural Gas Consumption Forecasting. Sustainability. 2020; 12 (16):6409.

Chicago/Turabian Style

Athanasios Anagnostis; Elpiniki Papageorgiou; Dionysis Bochtis. 2020. "Application of Artificial Neural Networks for Natural Gas Consumption Forecasting." Sustainability 12, no. 16: 6409.

Journal article
Published: 18 June 2020 in Research, Society and Development
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Sistemas de consórcio vem como uma alternativa para redução da evaporação da água do solo e consequentemente maior disponibilidade de águas para as plantas. O objetivo deste trabalho foi verificar a influência do consórcio entre a cultura do milho com a crotalária, determinando a evapotranspiração das culturas e avaliando o efeito da competição hídrica nas características produtivas da cultura do milho. O experimento foi realizado no campo experimental da Universidade do Estado de Mato Grosso (UNEMAT), composto por três tratamentos, sendo: T1 - milho solteiro (Zea mays L.), T2 - crotalária solteira (Crotalaria juncea L.), e T3 - milho cultivado em consórcio com crotalária. A evapotranspiração de referência (ETo) foi estimada pela metodologia proposta por Penman-Monteith FAO-56. A evapotranspiração da cultura (ETc) dos tratamentos foram determinadas diariamente através da variação de massa de lisímetros de pesagem, convertida em mm dia-1. A evaporação do solo foi determinada com a utilização de microlisímetros. Foram determinadas as fases fenológicas das culturas para a determinação da ETc nos diferentes estádios de desenvolvimento conforme recomendado pela FAO-56, sendo: Inicial (I), Desenvolvimento (II), Intermediária (III) e Final (IV). Os componentes da produtividade do milho foram avaliados no final do ciclo da cultura. A evaporação do solo foi reduzida em 43,91 mm (26,78%), e a transpiração reduziu em 19,64 mm (14,85%) quando utilizado o sistema de milho consorciado, em relação ao milho em cultivo solteiro. A ETc acumulada foi de 312,00; 436,16 e 422,38 mm, para o milho, crotalária e o consórcio, respectivamente. A produtividade foi de 6739,26 e 4571,85 kg ha-1, para o milho em cultivo solteiro e consorciado, respectivamente.

ACS Style

Diego Fernando Daniel; Rivanildo Dallacort; João Danilo Barbieri; Rafael Cesar Tieppo; Marco Antonio Camillo De Carvalho; William Fenner; Oscar Mitsuo Yamashita. Evapotranspiração e produtividade de milho safrinha consorciado com crotalária. Research, Society and Development 2020, 9, e890986196 -e890986196.

AMA Style

Diego Fernando Daniel, Rivanildo Dallacort, João Danilo Barbieri, Rafael Cesar Tieppo, Marco Antonio Camillo De Carvalho, William Fenner, Oscar Mitsuo Yamashita. Evapotranspiração e produtividade de milho safrinha consorciado com crotalária. Research, Society and Development. 2020; 9 (8):e890986196-e890986196.

Chicago/Turabian Style

Diego Fernando Daniel; Rivanildo Dallacort; João Danilo Barbieri; Rafael Cesar Tieppo; Marco Antonio Camillo De Carvalho; William Fenner; Oscar Mitsuo Yamashita. 2020. "Evapotranspiração e produtividade de milho safrinha consorciado com crotalária." Research, Society and Development 9, no. 8: e890986196-e890986196.

Review
Published: 18 May 2020 in Applied Sciences
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Background: Musculoskeletal disorders (MSDs) have long been recognized as the most common risks that operation of agricultural machineries poses, thus, undermining the ability to labor and quality of life. The purpose of this investigation was to thoroughly review the recent scholarly literature on ergonomics in agricultural mechanized operations; Methods: Electronic database research over the last ten years was conducted based on specific inclusion criteria. Furthermore, an assessment of the methodological quality and strength of evidence of potential risk factors causing MSDs was performed; Results: The results demonstrated that ergonomics in agriculture is an interdisciplinary topic and concerns both developed and developing countries. The machines with driving seats seem to be associated with painful disorders of the low back, while handheld machines with disorders of the upper extremities. The main roots of these disorders are the whole-body vibration (WBV) and hand-arm transmitted vibration (HATV). However, personal characteristics, awkward postures, mechanical shocks and seat discomfort were also recognized to cause MSDs; Conclusions: The present ergonomic interventions aim mainly at damping of vibrations and improving the comfort of operator. Nevertheless, more collaborative efforts among physicians, ergonomists, engineers and manufacturers are required in terms of both creating new ergonomic technologies and increasing the awareness of workers for the involved risk factors.

ACS Style

Lefteris Benos; Dimitrios Tsaopoulos; Dionysis Bochtis. A Review on Ergonomics in Agriculture. Part II: Mechanized Operations. Applied Sciences 2020, 10, 3484 .

AMA Style

Lefteris Benos, Dimitrios Tsaopoulos, Dionysis Bochtis. A Review on Ergonomics in Agriculture. Part II: Mechanized Operations. Applied Sciences. 2020; 10 (10):3484.

Chicago/Turabian Style

Lefteris Benos; Dimitrios Tsaopoulos; Dionysis Bochtis. 2020. "A Review on Ergonomics in Agriculture. Part II: Mechanized Operations." Applied Sciences 10, no. 10: 3484.

Review
Published: 17 May 2020 in Applied Sciences
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The advent of mobile robots in agriculture has signaled a digital transformation with new automation technologies optimize a range of labor-intensive, resources-demanding, and time-consuming agri-field operations. To that end a generally accepted technical lexicon for mobile robots is lacking as pertinent terms are often used interchangeably. This creates confusion among research and practice stakeholders. In addition, a consistent definition of planning attributes in automated agricultural operations is still missing as relevant research is sparse. In this regard, a “narrative” review was adopted (1) to provide the basic terminology over technical aspects of mobile robots used in autonomous operations and (2) assess fundamental planning aspects of mobile robots in agricultural environments. Based on the synthesized evidence from extant studies, seven planning attributes have been included: (i) high-level control-specific attributes, which include reasoning architecture, the world model, and planning level, (ii) operation-specific attributes, which include locomotion–task connection and capacity constraints, and (iii) physical robot-specific attributes, which include vehicle configuration and vehicle kinematics.

ACS Style

Vasileios Moisiadis; Naoum Tsolakis; Dimitris Katikaridis; Claus G. Sørensen; Simon Pearson; Dionysis Bochtis. Mobile Robotics in Agricultural Operations: A Narrative Review on Planning Aspects. Applied Sciences 2020, 10, 3453 .

AMA Style

Vasileios Moisiadis, Naoum Tsolakis, Dimitris Katikaridis, Claus G. Sørensen, Simon Pearson, Dionysis Bochtis. Mobile Robotics in Agricultural Operations: A Narrative Review on Planning Aspects. Applied Sciences. 2020; 10 (10):3453.

Chicago/Turabian Style

Vasileios Moisiadis; Naoum Tsolakis; Dimitris Katikaridis; Claus G. Sørensen; Simon Pearson; Dionysis Bochtis. 2020. "Mobile Robotics in Agricultural Operations: A Narrative Review on Planning Aspects." Applied Sciences 10, no. 10: 3453.

Journal article
Published: 07 May 2020 in Energies
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(1) Background: Forecasting of energy consumption demand is a crucial task linked directly with the economy of every country all over the world. Accurate natural gas consumption forecasting allows policy makers to formulate natural gas supply planning and apply the right strategic policies in this direction. In order to develop a real accurate natural gas (NG) prediction model for Greece, we examine the application of neuro-fuzzy models, which have recently shown significant contribution in the energy domain. (2) Methods: The adaptive neuro-fuzzy inference system (ANFIS) is a flexible and easy to use modeling method in the area of soft computing, integrating both neural networks and fuzzy logic principles. The present study aims to develop a proper ANFIS architecture for time series modeling and prediction of day-ahead natural gas demand. (3) Results: An efficient and fast ANFIS architecture is built based on neuro-fuzzy exploration performance for energy demand prediction using historical data of natural gas consumption, achieving a high prediction accuracy. The best performing ANFIS method is also compared with other well-known artificial neural networks (ANNs), soft computing methods such as fuzzy cognitive map (FCM) and their hybrid combination architectures for natural gas prediction, reported in the literature, to further assess its prediction performance. The conducted analysis reveals that the mean absolute percentage error (MAPE) of the proposed ANFIS architecture results is less than 20% in almost all the examined Greek cities, outperforming ANNs, FCMs and their hybrid combination; and (4) Conclusions: The produced results reveal an improved prediction efficacy of the proposed ANFIS-based approach for the examined natural gas case study in Greece, thus providing a fast and efficient tool for utterly accurate predictions of future short-term natural gas demand.

ACS Style

Konstantinos Papageorgiou; Elpiniki I. Papageorgiou; Katarzyna Poczeta; Dionysis Bochtis; George Stamoulis. Forecasting of Day-Ahead Natural Gas Consumption Demand in Greece Using Adaptive Neuro-Fuzzy Inference System. Energies 2020, 13, 2317 .

AMA Style

Konstantinos Papageorgiou, Elpiniki I. Papageorgiou, Katarzyna Poczeta, Dionysis Bochtis, George Stamoulis. Forecasting of Day-Ahead Natural Gas Consumption Demand in Greece Using Adaptive Neuro-Fuzzy Inference System. Energies. 2020; 13 (9):2317.

Chicago/Turabian Style

Konstantinos Papageorgiou; Elpiniki I. Papageorgiou; Katarzyna Poczeta; Dionysis Bochtis; George Stamoulis. 2020. "Forecasting of Day-Ahead Natural Gas Consumption Demand in Greece Using Adaptive Neuro-Fuzzy Inference System." Energies 13, no. 9: 2317.

Journal article
Published: 12 April 2020 in Sustainability
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Almost one billion people in the world still do not have access to electricity. Most of them live in rural areas of the developing world. Access to electricity in the rural areas of Sub-Saharan Africa is only 28%, roughly 600 million people. The financing of rural electrification is challenging and, in order to accomplish higher private sector investments, new innovative business models have to be developed. In this paper, a new approach in the financing of microgrid electrification activities is proposed and investigated. In this approach, agriculture related businesses take the lead in the electrification activities of the surrounding communities. It is shown that the high cost of rural electrification can be met through the increased value of locally produced products, and cross-subsidization can take place in order to decrease the cost of household electrification. The approach is implemented in a case study in Rwanda, through which the possibility of local agricultural cooperatives leading electrification activities is demonstrated.

ACS Style

George Kyriakarakos; Athanasios T. Balafoutis; Dionysis Bochtis. Proposing a Paradigm Shift in Rural Electrification Investments in Sub-Saharan Africa through Agriculture. Sustainability 2020, 12, 3096 .

AMA Style

George Kyriakarakos, Athanasios T. Balafoutis, Dionysis Bochtis. Proposing a Paradigm Shift in Rural Electrification Investments in Sub-Saharan Africa through Agriculture. Sustainability. 2020; 12 (8):3096.

Chicago/Turabian Style

George Kyriakarakos; Athanasios T. Balafoutis; Dionysis Bochtis. 2020. "Proposing a Paradigm Shift in Rural Electrification Investments in Sub-Saharan Africa through Agriculture." Sustainability 12, no. 8: 3096.

Journal article
Published: 19 March 2020 in Energies
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Photovoltaic Solar Energy (PSE) sector has sparked great interest from governments over the last decade towards diminution of world’s dependency to fossil fuels, greenhouse gas emissions reduction and global warming mitigation. Photovoltaic solar energy also holds a significant role in the transition to sustainable energy systems. These systems and their optimal exploitation require an effective supply chain management system, such as design of the network, collection, storage, or transportation of this energy resource, without disregarding a country’s certain socio-economic and political conditions. In Brazil, the adoption of photovoltaic solar energy has been motivated not only by the energy matrix diversification but also from the shortages, problems, and barriers that the Brazilian energy sector has faced, lately. However, PSE development is affected by various factors with high uncertainty, such as political, social, economic, and environmental, that include critical operational sustainability issues. Thus, an elaborate modelling of energy management and a well-structured decision support process are needed to enhance the performance efficiency of Brazilian PSE supply chain management. This study focuses on the investigation of certain factors and their influence on the development of the Brazilian PSE with the help of Fuzzy Cognitive Maps. Fuzzy Cognitive Map is an established methodology for scenario analysis and management in diverse domains, inheriting the advancements of fuzzy logic and neural networks. In this context, a semi-quantitative model was designed with the help of various stakeholders from the specific energy domain and three plausible scenarios were conducted in order to support a decision-making process on PSE sector development and the country’s economic potential. The outcome of this analysis reveals that the development of the PSE sector in Brazil is mainly affected by economic and political factors.

ACS Style

Konstantinos Papageorgiou; Gustavo Carvalho; Elpiniki I. Papageorgiou; Dionysis Bochtis; George Stamoulis. Decision-Making Process for Photovoltaic Solar Energy Sector Development using Fuzzy Cognitive Map Technique. Energies 2020, 13, 1427 .

AMA Style

Konstantinos Papageorgiou, Gustavo Carvalho, Elpiniki I. Papageorgiou, Dionysis Bochtis, George Stamoulis. Decision-Making Process for Photovoltaic Solar Energy Sector Development using Fuzzy Cognitive Map Technique. Energies. 2020; 13 (6):1427.

Chicago/Turabian Style

Konstantinos Papageorgiou; Gustavo Carvalho; Elpiniki I. Papageorgiou; Dionysis Bochtis; George Stamoulis. 2020. "Decision-Making Process for Photovoltaic Solar Energy Sector Development using Fuzzy Cognitive Map Technique." Energies 13, no. 6: 1427.

Review
Published: 11 March 2020 in Applied Sciences
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Background: Agriculture involves several harmful diseases. Among the non-fatal ones, musculoskeletal disorders (MSDs) are the most prevalent, as they have reached epidemic proportions. The main aim of this investigation is to systematically review the major risk factors regarding MSDs as well as evaluate the existing ergonomic interventions. Methods: The search engines of Google Scholar, PubMed, Scopus, and ScienceDirect were used to identify relevant articles during the last decade. The imposed exclusive criteria assured the accuracy and current progress in this field. Results: It was concluded that MSDs affect both developed and developing countries, thus justifying the existing global concern. Overall, the most commonly studied task was harvesting, followed by load carrying, pruning, planting, and other ordinary manual operations. Repetitive movements in awkward postures, such as stooping and kneeling; individual characteristics; as well as improper tool design were observed to contribute to the pathogenesis of MSDs. Furthermore, low back disorders were reported as the main disorder. Conclusions: The present ergonomic interventions seem to attenuate the MSDs to a great extent. However, international reprioritization of the safety and health measures is required in agriculture along with increase of the awareness of the risk factors related to MSDs.

ACS Style

Lefteris Benos; Dimitrios Tsaopoulos; Dionysis Bochtis. A Review on Ergonomics in Agriculture. Part I: Manual Operations. Applied Sciences 2020, 10, 1905 .

AMA Style

Lefteris Benos, Dimitrios Tsaopoulos, Dionysis Bochtis. A Review on Ergonomics in Agriculture. Part I: Manual Operations. Applied Sciences. 2020; 10 (6):1905.

Chicago/Turabian Style

Lefteris Benos; Dimitrios Tsaopoulos; Dionysis Bochtis. 2020. "A Review on Ergonomics in Agriculture. Part I: Manual Operations." Applied Sciences 10, no. 6: 1905.