This paper sets itself in a context of examining how IoT technology is disrupting and revolutionizing the monitoring and control of relative humidity in different spheres of smart cities with special reference to the enhancement of well-being in the information society. The authors discuss the current emergent research topics in IoT-based humidity sensors, wireless communication systems, and big data analytics for monitoring and controlling the humidity in real time. The paper also presents an outlook into various fields such as agriculture, healthcare, intelligent houses, industries, as well as the environment, and presents an indication of how managing humidity accurately enhances crop productivity, disease prevention, internal air quality, and the general wellbeing of the public. This also covers on the use of artificial intelligence and machine learning for IoT on analysis in terms of prediction and control. Admittedly, there are limitations associated with IoT including data security, compatibility, and power supply issues of the devices, etc. The future development of IoT as described in the paper includes improved sensors, edge computing, and the use of block-chain technology. Therefore, the authors find that IoT techniques for humidity measurement and management are effectively used in the development of healthier, comfortable, and sustainable environments in smart cities to enhance the quality of life.

Climate change impacts on drylands pose more vexing risks to socio-ecological systems, resulting in food security issues, biodiversity loss, and livelihood shifts in Africa. This study critically reviewed relevant literature to evaluate the complexities and feedback loops between the climate–drylands–food security (CDF) nexus, which helps assess tactics to attain sustainable dryland ecosystem management under the changing environment. Comprehensive CDF frameworks are explored for dryland dynamics, ecosystem services, and food security (FS), and current high-precision ecosystem observation networks are used to detect regional-level climate variability and identify hotspots. In addition, this review also examines challenges and uncertainties for CDF systems and effective agrarian innovations as a way forward. To bridge the gap from science to policy making in the CDF nexus, it is vital to enhance the impacts and feedbacks of ecohydrological processes on agrarian production, ecosystem service tradeoffs and their effects on livelihoods, and regional development and preservation by optimization of the ecological water security pattern. This state-of-the-art assessment uses acquired information and knowledge to conceptually evaluate the past, current, and future impacts and risks and facilitates decision making through the delivery of long-term sustainability and socio-ecological resilience.

Complete water accounting (WA) and crop water productivity (CWP) analysis is crucial for evaluating water use efficiency (WUE). This study aims to evaluate the contributions of hydro-meteorological factors to the changes of WA and CWP and subsequent WUE based on the data from 2009–2020 in the Nile River Basin (NRB), East Africa (EA). The Mann-Kendall (MK) statistical test and Sen’s slope estimator were applied to detect the trends of climatic factors, and the AquaCrop model was used to simulate the crop yields in response to water balance and consumption based on crop physiological, soil water, and salt budget concepts. For the years 2012 and 2019, the mean of climatic water deficit P − ETa was 71.03 km³ and 37.03 km³, respectively, which was expected to rise to ~494.57 km³ by 2050. The results indicated that the basin water budget was unbalanced due to the coupled impact of year-to-year hot and dry conditions and increase in water abstraction, an indication of water deficit or stress. CWP and WUE increased during the study period with different changing patterns. CWP was also found to correlate to the yield of major crops (p-value > 0.05). It was concluded that climatic factors influenced the crop yield, CWP, and WUE in the study area. Thus, the improvement of CWP and WUE should rely on advanced water-saving innovations. The findings of this study could help water managers to improve water productivity by focusing on water account potentials and creating regional advantages by deploying water in combination with surplus flow from upstream to downstream consumption.

Artificial Intelligence (AI) is increasingly pivotal in addressing global challenges by integrating technological advancements into environmental conservation and societal development. This paper explores the dual nature of AI's role—its capacity to foster sustainability and societal improvement, alongside the challenges it introduces. The research highlights AI applications in environmental management, such as optimizing resource use, monitoring ecosystems, and enhancing renewable energy efficiency. In societal contexts, AI's transformative potential extends to healthcare, education, and urban planning, fostering equitable access to essential services. However, significant barriers, including data scarcity, limited technical infrastructure, regulatory gaps, and socio-economic inequalities, hinder widespread AI adoption. By analyzing secondary data from recent literature, this study identifies critical challenges and presents actionable policy recommendations to ensure inclusive, ethical, and impactful AI integration. The findings underscore the urgency of collaborative efforts among governments, industries, and academia to leverage AI for achieving the United Nations Sustainable Development Goals (SDGs) and addressing pressing global issues.