Eleni Symeonaki

Considering that the fusion of education and technology has delivered encouraging outcomes, things are becoming more challenging for higher education as students seek experiences that bridge the gap between theory and their future professional roles. Giving priority to the above issue, this study presents methods and results from activities assisting engineering students to utilize recent machine-learning techniques for tackling the challenge of water resource preservation. Cost-effective, innovative hardware and software components were incorporated for monitoring the proper operation of the corresponding agricultural equipment (such as electric pumps or water taps), and suitable educational activities were developed involving students of agricultural engineering. According to the evaluation part of the study being presented, the implementation of a machine-learning system with sufficient performance is feasible, while the outcomes derived from its educational application are significant, as they acquaint engineering students with emerging technologies entering the scene and improve their capacity for innovation and cooperation. The study demonstrates how emerging technologies, such as IoT, ML, and the newest edge-AI techniques can be utilized in the agricultural industry for the development of sustainable agricultural practices. This aims to preserve natural resources such as water, increase productivity, and create new jobs for technologically efficient personnel.

The potential application of the digital twins concept and its principles to all industries, including agriculture, has recently been the subject of considerable research interest. Since livestock farming is one of the mainstays of the agricultural industry, contributing to food security as well as employment and income generation, digital twins appear to be a promising technology to address issues related to the intensive nature of livestock production systems, which are typically characterized by high levels of input and output. The objective of this study is to identify and analyze the latest scientific and technological contributions in the field of digital twins technology, with a view to its adoption and assimilation in livestock production systems in the context of Agriculture 5.0. In particular, the aim of this study is to synthesize the existing research and identify the opportunities and open issues related to the implementation of digital twins in livestock production systems. The results derived in the literature review indicate that digital twins is still in the early stages of development in livestock farming, but it has the potential to transform the industry. As Agriculture 5.0 evolves and the digital twins technology matures, it is expected to play an increasingly important role in the livestock farming industry.

Background: Sustainable design means to base design on any systems and methods that can fulfill any of the sustainability goals: reducing waste, recycling plastics, upcycle materials, etc., and having less of an impact on the environment. Therefore, a challenge arises: how to design products based on sustainable design. This research presents a case study, about how students in a university’s design department, used sustainability practices in their projects, to adopt sustainability as a major aspect during the design process of a product. Methods: The researchers used STEM methodologies to educate and guide the students to adopt recycling and upcycling practices to design and develop an educational mobile robot for Educational Robotics and Mechatronics applications. Results: Students were encouraged to develop their problem-solving approaches when developing their designed robots, for a mechatronics project given to them. In this way, the researchers fostered the active and motivated participation of students; an increased interest was found related to several factors, including challenge, competition, group participation, and more. Conclusions: This research aimed to evidence the use of upcycled and recycled materials in product development to fulfill some of the sustainability goals. The research’s results were very promising and has sparked an ongoing research.

This work presents an approach for wirelessly monitoring the indoor temperature, relative humidity, and carbon dioxide (CO₂) concentration parameters affecting the microclimate of the Holy Cross hermitage, which extends into a small cave located in the Olympus area of Greece and maintains remarkable wall paintings dated back to 1339 A.D. The results indicate that the methodology applied was effective enough in maintaining a long-term monitoring process and, as a result, comprehending the ambient conditions of the hermitage with regard to its microclimate. In this context, it would be possible to identify any imminent hazards in time and therefore plan the required conservation actions.

Resource management in agriculture is considered a pivotal issue because greenhouse farming and agriculture-related activities generate about 10–29% of all global greenhouse gas emissions. The problem of high greenhouse gas emissions is still unresolved due to the rapid expansion of arable land to meet global food demand. The purpose of this systematic literature review was to generate new perspectives and insights regarding the development of resource management and optimized environments in greenhouses, thereby lowering energy requirements and CO₂ emissions. This review sought to answer what technologies and inventions could be used to achieve zero greenhouse gas emissions through efficient energy-saving mechanisms while considering their technical and economic viability. The synthesis of the findings led to several themes which included energy-saving techniques for greenhouses, systems that reduced unfavorable external conditions and renewable energy systems. Other themes identified regarded energy storage systems, systems for managing conditions in greenhouses, carbon capture and storage, and factors influencing the performance of different technologies to enhance resource management and ensure zero carbon emissions. The findings also revealed various technologies used in the design of energy-saving techniques in greenhouses including proportional–integral–derivatives (PID), fuzzy, artificial neural networks, and other intelligent algorithms. Additionally, technologies that were a combination of these algorithms were also examined. The systems that reduced unfavorable external conditions included the use of insulation panels and intelligent shading systems. Greenhouse covers were also optimized by smart glass systems, sensors, Internet of Things (IoT), and Artificial Intelligence (AI) systems. Renewable energy systems included PV (solar) panels, wind turbines, and geothermal electricity. Some of the thermal energy storage systems widely studied in recent research included underground thermal energy storage (UTES) (for seasonal storage), phase-change materials (PCMs), and water tanks, which are used to address short-term shortages and peak loads. The adoption of the various technologies to achieve the above purposes was constrained by the fact that there was no isolated technology that could enable agricultural producers to achieve zero energy, zero emissions, and optimal resource utilization in the short term. Future research studies should establish whether it is economical for large agricultural companies to install smart glass systems and infrastructure for slow fertilizer release and carbon capture in greenhouse structures to offset the carbon footprint.

The focus of this review paper was to investigate innovations currently employed to capture and use greenhouse gases produced within livestock farms for energy production and expected future directions. The methods considered for data collection regarded a systematic review of the literature, where 50 journal articles were critically reviewed. The main findings identified that the conventional method used in transforming livestock agriculture greenhouse gases into energy regards the combustion of biogas. However, emerging methods encompass microbial fuel cells, dry biogas reforming, steam biogas reforming, auto thermal Chemical Looping Reforming (CLRa), and gas-to-liquid methods that convert methane to liquid hydrocarbons. The conclusions from the review are that there is a potential to integrate these methods in livestock agriculture in order to generate energy from greenhouse emissions and reduce the reliance on fossil fuels.

Integrated farm management (IFM) is promoted as a whole farm approach toward Agriculture 4.0, incorporating smart farming technologies for attempting to limit livestock production’s negative impacts on the environment while increasing productivity with regard to the economic viability of rural communities. The Internet of Things (IoT) may serve as an enabler to ensure key properties—such as interconnectivity, scalability, agility, and interoperability—in IFM systems so that they could provide object-based services while adapting to dynamic changes. This paper focuses on the problem of facilitating the management, processing, and sharing of the vast and heterogeneous data points generated in livestock facilities by introducing distributed IoT middleware as the core of a responsive and adaptive service-oriented IFM system, specifically targeted to enable smart livestock farming in view of its unique requirements. The proposed IoT middleware encompasses the context-awareness approach via the integration of a flexible ontology-based structure for modeling and reasoning. The IoT middleware was assessed in actual conditions on the grounds of a case study for smart control of the thermal environment in a medium-sized pig farming facility. As derived from the obtained evaluation results, the system appears to perform quite satisfactorily in terms of computational performance as well as ontology coherence, consistency, and efficiency.

Due to the dynamic nature of the agricultural industry, educators and their institutions face difficult challenges as they try to keep pace with future demands for knowledge and skilled workers. On the other hand, computational thinking (CT) has drawn increasing attention in the field of science, technology, engineering, and mathematics (STEM) education at present and, as advanced technologies and tools emerge, it is imperative for such innovations to be sustained with knowledge and skill among STEM educators and practitioners. The present case study aims to explore the relation between CT, STEM and agricultural education training (AET) in a Greek vocational training institute (IEK), the Agriculture IEK of Metamorfosis city (IEKMC), which is active in agriculture education. The research methodology is utilized according the positivist philosophical approach through data acquisition employing a questionnaire and the quantitative (statistical) analysis of data collected. The sample consists of IEKMC educators and students selected based on simple random sampling. Based on the participants belief that CT and STEM philosophy add value in the learning process, it focuses on the application of knowledge in the real world (students) and problem solving using new technologies (educators). Educators consider “experiments” as the most significant educational tool for problem solving in teaching practice. Students rate Greek Agriculture Education and Training (GAET) higher than educators. However, the participants evaluate GAET very low due to the lack of new innovative teaching methods being introduced. Finally, there is great interest in the implementation of CT and STEM in the European Union (EU) by students and educators.