The economy, unemployment, and job creation of South Africa heavily depend on the growth of the agricultural sector. With a growing population of 60 million, there are approximately 4 million small-scale farmers (SSF) number, and about 36,000 commercial farmers which serve South Africa. The agricultural sector in South Africa faces challenges such as climate change, lack of access to infrastructure and training, high labour costs, limited access to modern technology, and resource constraints. Precision agriculture (PA) using AI can address many of these issues for small-scale farmers by improving access to technology, reducing production costs, enhancing skills and training, improving data management, and providing better irrigation infrastructure and transport access. However, there is a dearth of research on the application of precision agriculture using artificial intelligence (AI) by small scale farmers (SSF) in South Africa and Africa at large. The preferred reporting items for systematic reviews and meta-analyses (PRISMA) and Bibliometric analysis guidelines were used to investigate the adoption of precision agriculture and its socio-economic implications for small-scale farmers in South Africa or the systematic literature review (SLR) compared various challenges and the use of PA and AI for small-scale farmers. The incorporation of AI-driven PA offers a significant increase in productivity and efficiency. Through a detailed systematic review of existing literature from inception to date, this study examines 182 articles synthesized from two major databases (Scopus and Web of Science). The systematic review was conducted using the machine learning tool R Studio. The study analyzed the literature review articled identified, challenges, and potential societal impact of AI-driven precision agriculture.

Weather is almost inevitable and plays an important role in determining the duration of construction projects. The construction industry ultimately thrives upon the physical input, put in by the labours. The majority of the construction projects are executed in the outdoor environment and hence face a high impact of weather conditions. This study therefore evaluated the influence of weather conditions on construction workers’ productivity in Jos, Plateau State and proceeded to make recommendations geared towards the improvement of construction workers’ productivity in Jos. The study was conducted through the direct observation method. Three hundred and ninety-six (396) works were purposively sampled in selected working sites. The outcome shows that during dry weather, there was considerably less significant productivity of manual excavation. In contrast, a large increase in blockwork and plasterwork productivity was observed with a percentage difference of 33%, 56.3% and 61%, respectively. On the other hand, during wet weather conditions, the labour productivity for manual excavation increases, whereas it decreases for block work and plasterwork with percentages difference of 58%, 40% and 47%, respectively. Besides, relative humidity and wind speed have no impact on labours’ productivity in dry and wet weather. Besides, the temperature has the most decisive impact on workers’ productivity. Moreover, wind speed and humidity have a lower influence on workers’ productivity. The construction industry stakeholder in Jos, Nigeria, would benefit from this study’s recommendations for reducing the influence of weather on the building sector. Besides, the output can be extended to other regions having similar characteristics.

Electrical energy is known as an essential part of our day-to-day lives. Renewable energy resources can be regenerated through the natural method within a reasonably short time and can be used to bridge the gap in extended power outages. Achieving more renewable energy (RE) than the low levels typically found in today’s energy supply network will entail continuous additional integration efforts into the future. This study examined the impacts of integrating renewable energy on the power quality of transmission networks. This work considered majorly two prominent renewable technologies (solar photovoltaic and wind energy). To examine the effects, IEEE 9-bus (a transmission network) was used. The transmission network and renewable sources (solar photovoltaic and wind energy technologies) were modelled with MATLAB/SIMULINK^®. The Newton-Raphson iteration method of solution was employed for the solution of the load flow owing to its fast convergence and simplicity. The effects of its integration on the quality of the power supply, especially the voltage profile and harmonic content, were determined. It was discovered that the optimal location, where the voltage profile is improved and harmonic distortion is minimal, was at Bus 8 for the wind energy and then Bus 5 for the solar photovoltaic source.

This paper presents a practical approach to empowering software entrepreneurship in Saudi Arabia through a unique course offered by the Software Engineering department at Prince Sultan University. The course, SE495 Emergent Topics in Software Engineering: Software Entrepreneurship, combines software engineering and entrepreneurship to equip students with the necessary skills to develop innovative software solutions that solve real-world problems. The course covers a range of topics, including platform development, market research, and pitching to investors, and features guest speakers from the industry. By the end of the course, students will have gained a deep understanding of the software development process and its intersection with entrepreneurship and will be able to develop a working prototype of a software solution that solves a real-world problem. The course’s practical approach ensures that students are well-prepared to navigate the complexities of the digital and software sectors and succeed in an ever-changing business landscape.

This study evaluates the influence of quality certificates on sustainable food production in Poland, considering economic, social, and environmental dimensions. Analyzing 25 different certificates, the research explores their criteria, procedures, and costs across various food product categories, including meat, fish, and plant-based products. The study provides a detailed review of certification processes, from initiation to audits and inspections. It identifies both commonalities and differences among certificates, each addressing unique aspects such as environmental impact, worker rights, and product origins. Despite the diversity in standards and procedures, the study underscores the need for standardized international criteria to improve transparency and meet consumer expectations, highlighting the significant role of quality certificates in advancing sustainable food production.

Background: The COVID-19 pandemic has had a substantial economic and psychological impact on workers in Saudi Arabia. The objective of the study was to assess the effects of the COVID-19 epidemic on the financial and mental well-being of Saudi employees in the Kingdom of Saudi Arabia. Purpose: The COVID-19 epidemic has resulted in significant economic and societal ramifications. Current study indicates that the pandemic has not only precipitated an economic crisis but has also given rise to several psychological and emotional crises. This article provides a conceptual examination of how the pandemic impacts the economic and mental health conditions of Saudi workers, based on contemporary Structural Equation Modeling (SEM) models. Method: The current study employed a qualitative methodology and utilized a sample survey strategy. The data was gathered from Saudi workers residing in major cities of Saudi Arabia. The samples were obtained from professionals such as managers, doctors, and engineers, as well as non-professionals like unskilled and low-skilled laborers, who are employed in various public and private sectors. A range of statistical tools, including Descriptive statistics, ANOVA, Pearson’s Correlation, Factor analysis, Reliability test, Chi-square test, and regression approach, were employed to analyze and interpret the results. Result: According to the data, the pandemic has caused a wide range of economic problems, including high unemployment and underemployment rates, income instability, and different degrees of pressure on workers to find work. Feelings of insecurity (about food and environmental safety), worry, dread, stress, anxiety, depression, and other mental health concerns have been generated by these challenges. The rate of mental health decline differs among demographics. Conclusions: The COVID-19 pandemic has universally affected all aspects of our lives worldwide. It resulted in an extended shutdown of educational institutions, factories, offices, and businesses. Without a question, it has profoundly transformed the work environment, professions, and lifestyles of billions of individuals worldwide. There is a high occurrence of poor psychological well-being among Saudi workers. However, it has been demonstrated that both economic health and mental health interventions can effectively alleviate the mental health burden in this population.