Background: The Internet of Things (IoT) interconnects humans to things, things to things, and humans to humans, streamlining routine activities via the Internet for time and cost savings, and heightened productivity. Despite a global uptick in IoT adoption, Limpopo province’s agricultural sector faces a significant lag in embracing and utilizing IoT technologies. Objectives: The goal of the study was to determine the factors that may determine the adoption and use of IoT within the agricultural sector in Limpopo province. Method: A qualitative study was carried out using Unified Theory Acceptance and Usage of Technology (UTAUT) as the theoretical lens. Data were collected using interviews, observations, and document reviews from the Limpopo agricultural sector participants. Analysis was performed by means of thematic analysis. Results: Priori themes for this study namely, organisational support, cost, knowledge gap, security and policy were confirmed as significant in the adoption of IoT in the Limpopo agricultural sector. Monitoring, control, perceived value, and risk emerged as new themes in the adoption of IoT. Conclusion: For Limpopo agricultural sector to be transformed from manual methods of conducting agricultural activities to the automated method, they will need support enshrined in policies dealing with cost, knowledge transfers as well as security assurances about the use of modern technology such as IoT. Contribution: A study exploring IoT adoption in Limpopo’s agricultural sector promises regional transformation. The Internet of Things can revolutionise practices with real-time monitoring, data-driven decision-making, boosting crop yields, resource efficiency, and sustainability. It empowers smallholder farmers, stimulates rural development, offers valuable data for policymakers, and enhances economic viability in addressing challenges like water scarcity, climate change, and market competitiveness, ultimately improving livelihoods in Limpopo province.

Over the past few years, the notion of Industry 5.0 has emerged as a subsequent phase in industrial revolution. The distinguishing features of Industry 5.0 encompass advanced technologies that include Internet of Things (IoT), artificial intelligence (AI), and robotics integrated into manufacturing processes, resulting in amplified automation and efficiency alongside productivity. However, this ever-growing reliance on digital technologies has accentuated the significance of robust cybersecurity measures like never before. Industry 5.0 distinguishes itself from its predecessor, Industry 4.0, in that it prioritizes human labour over automation and digitalization to foster sustainable and resilient industrial production practices. However, the convergence of cybersecurity issues with this novel paradigm may pose considerable challenges going forward, making a comprehensive analysis of security conditions across both industry paradigms essential for devising effective solutions addressing potential threats. To gain insight into such developments within contemporary industrial transformations as they pertain to cybersecurity concerns during the transition period from Industries 4.0 to Industries 5.0, this chapter conducts a review drawing on numerous academic resources regarding best practices in these domains overall. The resulting findings are analyzed by extracting key themes emanating from multiple research streams before synthesizing them into broader frameworks.

Limpopo, one of South Africa's nine provinces, is mostly rural, where agriculture serves as the primary occupation for around 89 percent of the total population. Agriculture relies on water, making it its most valuable asset. Through irrigation, water is supplied to crops for growth, frost control, and crop cooling. Irrigation can occur naturally, as with precipitation, or artificially, as with sprinklers. However, artificial irrigation is wasteful as it is regulated and monitored through human intervention, leading to water scarcity which is one of the obstacles that threatens the agricultural sector in the province of Limpopo. A machine learning precipitation prediction algorithm optimizes water usage. The paper also describes a system with multiple sensors that detect soil parameters, and automatically irrigate land based on soil moisture by switching the motor on/off. The objective of this paper is to develop an automated farming irrigation system that is both efficient and effective, with the intention of contributing to the resolution of the water crisis in the province of Limpopo. The proposed solution ought to be capable of decreasing labour hours, generating cost savings, ensuring consistent and efficient water usage, and gathering informed data to inform future research. Thus, farmers will have greater access to information regarding when to irrigate, how much water to use, weather alerts, and recommendations. In acquiring these, the ARIMA model was applied alongside DSRM for implementing the mobile application. The results obtained indicate that the use of AI and IoT (AIoT) in agriculture can improve operational efficiency with reduced human intervention as there is real-time data acquisition with real-time processing and predictions.

Background: South African universities are dealing with concerning socio-economic issues and budgetary limits that affect university operations negatively. It is no longer viable for most universities to purchase and maintain information technology (IT) infrastructure systems while also keeping up with the ever-changing technology across the world. Objectives: The aim of this article is to explore the benefits that come with infrastructure as a service (IaaS), as compared to the on-premises model that is currently used by most South African universities. Method: This article adopts both transaction cost theory (TCT) and diffusion of innovation theory (DOI) as the underpinning theories. The interpretivist paradigm was applied to gain a comprehensive understanding of how university management perceives IaaS adoption. Results: The results introduce three new and critical factors that need to be considered by university managers whenever they want to move their on-premises IT model to cloud IaaS: trust, security and attitude. Conclusion: The research finds that IaaS offers advantages in scalability, flexibility, accessibility and on-demand deployment. These findings underscore the importance of addressing barriers to IaaS adoption within the specific context of South African universities. Contribution: The findings of this article add to the cloud computing literature, by presenting a new model that IT decision-makers can utilise when considering moving their on-premises IT infrastructure to IaaS in South African universities. The article recommends that future research could expand the number of universities from which data are collected.