A Cloud-Based with Microcontroller Platforms System Designed to Educate Students within Digitalization and the Industry 4.0 Paradigm

Mijailovic, D Zeljko; Đorđević, Aleksandar; Stefanović, Miladin; Vidojevic, Dejan; Gazizulina, Albina; Projović, Damir

doi:10.3390/su132212396

Cited by 7 publications

(5 citation statements)

References 43 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The suggested approach was adjusted to introduce and foster communication among students about the fundamentals of machine learning, which is an essential process for many agricultural operations and are connected with other contemporary technological methods of the digital era, such as networking. 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.…”

Section: Educational Aspectsupporting

confidence: 73%

“…Apart from the more conventional educational approaches dealing with engineering with electromechanical [39,40] and basic IoT [41] solutions applied in modern industry and agriculture, various educational projects aim to improve individuals' AI literacy. According to recent research [42], preliminary courses on AI are offered at various educational levels, from elementary school [43] and secondary education [44,45] to higher education [46,47].…”

Section: Related Work and Rationalementioning

confidence: 99%

See 1 more Smart Citation

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

Kondoyanni,

Loukatos,

Arvanitis

et al. 2024

Sustainability

View full text Add to dashboard Cite

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.

show abstract

Section: Educational Aspectsupporting

confidence: 73%

Section: Related Work and Rationalementioning

confidence: 99%

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

Kondoyanni,

Loukatos,

Arvanitis

et al. 2024

Sustainability

View full text Add to dashboard Cite

show abstract

“…Moreover, IT project management excellence enables organizations to leverage technology solutions to address sustainability challenges and opportunities. For example, the adoption of cloud computing [35], data analytics, and Internet of Things (IoT) [36,37] technologies can help organizations optimize energy consumption, improve agility, and enhance resource efficiency in their operations [38][39][40][41].…”

Section: Key Dimensions Of It Project Management Excellencementioning

confidence: 99%

Data-Driven Decision Making for Sustainable IT Project Management Excellence

Pantović,

Vidojević,

Vujičić

et al. 2024

Sustainability

Self Cite

View full text Add to dashboard Cite

In today’s rapidly evolving technological landscape, effective management of information technology (IT) projects is paramount for organizational success. However, ensuring sustainability in IT project management remains a persistent challenge. This paper proposes a novel approach centered on data-driven strategies to enhance sustainability and excellence in IT project management. By harnessing the power of data analytics, organizations can derive actionable insights to optimize resource allocation, mitigate risks, and streamline project workflows. The integration of data-driven decision making processes enables project managers to make informed choices, fostering adaptability and resilience in the face of dynamic project environments. This research explores the utilization of IT software project performance metrics and historical project data to fuel analysis of how strategies drive business sustainability. Moreover, this paper examined these dimensions with the help of advanced analytics techniques such as multiple linear regression. By aligning IT project management practices with business sustainability objectives, organizations can enhance project success rates, while minimizing adverse environmental impacts and resource consumption. Prospectively, this kind of research should expand to determining factors for the adoption of data-driven strategies to empower organizations to achieve sustainable IT project management excellence, ensuring long-term competitiveness and value creation in a digitalized world.

show abstract

“…It must be noted that, although there are studies comparing the effects of using robotics in elementary and secondary schools, there are less empirical studies on the real effect of applying robotics in higher education [55]. Furthermore, recent analysis of the literature and the situation in monitoring and managing in the agriculture and ecology field, indicated that there are few special education courses regarding these issues [71]. These remarks make the contribution of the proposed approach even more beneficial for the research community.…”

Section: Educational Impactmentioning

confidence: 99%

Using Open Tools to Transform Retired Equipment into Powerful Engineering Education Instruments: A Smart Agri-IoT Control Example

et al. 2022

View full text Add to dashboard Cite

People getting involved with modern agriculture should become familiar with and able to exploit the plethora of cutting-edge technologies that have recently appeared in this area. The contribution of the educational robotics in demystifying new scientific fields for K-12 students is remarkable, but things become more challenging when trying to discover efficient practices for higher education. Indeed, there is an apparent need for pilot examples facilitating students’ professional skills acquisition and thus matching the potential of the actual systems used in the modern agricultural premises. In this regard, this work discuses laboratory experiences while implementing an automatic airflow control system of convincing size and role capable for remote configuration and monitoring. This non-conventional robotic example exploits retired electromechanical equipment, from an old farm, and revives it using modern widely available microcontrollers, smart phones/tablets, network transceivers, motor drivers, and some cheap and/or custom sensors. The contribution of the corresponding software parts to this transformation is of crucial importance for the success of the whole system. Thankfully, these parts are implemented using easy-to-use programming tools, of open and free nature at most, that are suitable for the pairing credit-card-sized computer systems. The proposed solution is exhibiting modularity and scalability and assists students and future professionals to better understand the role of key elements participating in the digital transformation of the agricultural sector. The whole approach has been evaluated from both technical and educational perspective and delivered interesting results that are also reported.

show abstract

A Cloud-Based with Microcontroller Platforms System Designed to Educate Students within Digitalization and the Industry 4.0 Paradigm

Cited by 7 publications

References 43 publications

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

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

Data-Driven Decision Making for Sustainable IT Project Management Excellence

Using Open Tools to Transform Retired Equipment into Powerful Engineering Education Instruments: A Smart Agri-IoT Control Example

Contact Info

Product

Resources

About