Enhanced Robots as Tools for Assisting Agricultural Engineering Students’ Development

Abstract

Inevitably, the rapid growth of the electronics industry and the wide availability of tailored programming tools and support are accelerating the digital transformation of the agricultural sector. The latter transformation seems to foster the hopes for tackling the depletion and degradation of natural resources and increasing productivity in order to cover the needs of Earth’s continuously growing population. Consequently, people getting involved with modern agriculture, from farmers to students, should become familiar with and be able to use and improve the innovative systems making the scene. At this point, the contribution of the STEM educational practices in demystifying new areas, especially in primary and secondary education, is remarkable and thus welcome, but things become quite uncertain when trying to discover efficient practices for higher education, and students of agricultural engineering are not an exception. Indeed, university students are not all newcomers to STEM and ask for real-world experiences that better prepare them for their professional careers. Trying to bridge the gap, this work highlights good practices during the various implementation stages of electric robotic ground vehicles that can serve realistic agricultural tasks. Several innovative parts, such as credit card-sized systems, AI-capable modules, smartphones, GPS, solar panels, and network transceivers are properly combined with electromechanical components and recycled materials to deliver technically and educationally meaningful results.

Adding Machine-Learning Functionality to Real Equipment for Water Preservation: An Evaluation Case Study in Higher Education

“…It must be noted that, based on the literature review and the current state of agricultural management, it can be inferred that there are limited specialized educational courses addressing these concerns [41]. The findings presented align with and build upon previous educational discoveries in the field [63,66,86], as they fulfill the objectives of agri-food professionals involved in the shift towards sustainable agriculture. Indeed, according to the study presented in [87], upcoming professionals require skills that foster an attitude based on diversity and the inclusion of various information, methods, and experiences, along with the ability to respond and proactively engage in a dynamic world.…”

“…In all instances, the configuration was kept as open and inexpensive as possible to demonstrate high modularity and reusability of the units. This approach enables various educationally meaningful experimentation activities [63]. The survey results suggest that involvement in the entire activity was helpful for comprehending fundamental hardware and software topics, as well as for understanding the role of embedded systems (Figure 11a), and the proposed activities exhibit to be highly relevant to their courses at the university (Figure 10a).…”

“…Indeed, the CBL model has been applied to a large extend in higher education for groups of undergraduate students [58][59][60], and postgraduate students [61] and the results were positive, showing that the participants came up with innovative ideas to resolve challenges and improved skills and competencies. The benefits of the PBL [3] and CL [62] approaches, in terms of practicality and methodology, can be combined [63] and reinforced by the CBL technique to maximize the educational outcomes. As stated by Sukacke et al [64] the implementation of active learning methodologies in education, such as PBL and more recently CBL, has become the new norm, especially in engineering universities, preparing future engineers for their professional careers.…”

Physical Robots in Education: A Systematic Review Based on the Technological Pedagogical Content Knowledge Framework

“…For example, integrating robotics and AI in agriculture can significantly enhance sustainability by optimizing resource usage and improving crop yields. This is supported by recent studies such as those by Loukatos and Kondoyanni [58], who explore the potential of electronics and AI in promoting sustainable agricultural practices. Therefore, it is essential for future research to consider these sectors to provide a comprehensive understanding of the impact of robotics across different industries, including those crucial for sustainable development.…”

Automating Seedling Counts in Horticulture Using Computer Vision and AI

“…Therefore, leveraging machine learning and computer vision algorithms to count crops in images or video feeds automatically is becoming more popular due to its automation capabilities. Similarly, experimental robotic vehicles have emerged as key players, demonstrating their ability to efficiently navigate through plantation lines by seamlessly integrating machine vision with GPS information [20]. In addition to this, other platforms have been designed for remote plant inspections, leveraging high-quality thermal imagery data to identify potential issues and ensure optimal plant health [21].…”