As the global population grows, and urbanization becomes more prevalent, cities often struggle to provide convenient, secure, and sustainable lifestyles due to the lack of necessary smart technologies. Fortunately, the Internet of Things (IoT) has emerged as a solution to this challenge by connecting physical objects using electronics, sensors, software, and communication networks. This has transformed smart city infrastructures, introducing various technologies that enhance sustainability, productivity, and comfort for urban dwellers. By leveraging Artificial Intelligence (AI) to analyze the vast amount of IoT data available, new opportunities are emerging to design and manage futuristic smart cities. In this review article, we provide an overview of smart cities, defining their characteristics and exploring the architecture of IoT. A detailed analysis of various wireless communication technologies employed in smart city applications is presented, with extensive research conducted to determine the most appropriate communication technologies for specific use cases. The article also sheds light on different AI algorithms and their suitability for smart city applications. Furthermore, the integration of IoT and AI in smart city scenarios is discussed, emphasizing the potential contributions of 5G networks coupled with AI in advancing modern urban environments. This article contributes to the existing literature by highlighting the tremendous opportunities presented by integrating IoT and AI, paving the way for the development of smart cities that significantly enhance the quality of life for urban dwellers while promoting sustainability and productivity. By exploring the potential of IoT, AI, and their integration, this review article provides valuable insights into the future of smart cities, demonstrating how these technologies can positively impact urban environments and the well-being of their inhabitants.

The increasing global demand for seafood underscores the necessity for sustainable aquaculture practices. However, several challenges, including rising operational costs, variable environmental conditions, and the threat of disease outbreaks, impede progress in this field. This review explores the transformative role of the Artificial Intelligence of Things (AIoT) in mitigating these challenges. We analyse current research on AIoT applications in aquaculture, with a strong emphasis on the use of IoT sensors for real-time data collection and AI algorithms for effective data analysis. Our focus areas include monitoring water quality, implementing smart feeding strategies, detecting diseases, analysing fish behaviour, and employing automated counting techniques. Nevertheless, several research gaps remain, particularly regarding the integration of AI in broodstock management, the development of multimodal AI systems, and challenges regarding model generalization. Future advancements in AIoT should prioritise real-time adaptability, cost-effectiveness, and sustainability while emphasizing the importance of multimodal systems, advanced biosensing capabilities, and digital twin technologies. In conclusion, while AIoT presents substantial opportunities for enhancing aquaculture practices, successful implementation will depend on overcoming challenges related to scalability, cost, and technical expertise, improving models’ adaptability, and ensuring environmental sustainability.

Implantable electrodes represent a groundbreaking advancement in nervous system research, providing a pivotal tool for recording and stimulating human neural activity. This capability is integral for unraveling the intricacies of the nervous system’s functionality and for devising innovative treatments for various neurological disorders. Implantable electrodes offer distinct advantages compared to conventional recording and stimulating neural activity methods. They deliver heightened precision, fewer associated side effects, and the ability to gather data from diverse neural sources. Crucially, the development of implantable electrodes necessitates key attributes: flexibility, stability, and high resolution. Graphene emerges as a highly promising material for fabricating such electrodes due to its exceptional properties. It boasts remarkable flexibility, ensuring seamless integration with the complex and contoured surfaces of neural tissues. Additionally, graphene exhibits low electrical resistance, enabling efficient transmission of neural signals. Its transparency further extends its utility, facilitating compatibility with various imaging techniques and optogenetics. This paper showcases noteworthy endeavors in utilizing graphene in its pure form and as composites to create and deploy implantable devices tailored for neural recordings and stimulations. It underscores the potential for significant advancements in this field. Furthermore, this paper delves into prospective avenues for refining existing graphene-based electrodes, enhancing their suitability for neural recording applications in in vitro and in vivo settings. These future steps promise to revolutionize further our capacity to understand and interact with the neural research landscape.

Uca bengaliCrane, 1975 females have two small feeding claws but males have one small feeding claw and another big claw used for waving and fights. On the basis of video recordings of feeding motions and duration, and morphometric measurements of body size (measured as carapace width) and feeding claw size (measured as dactyl length and width), differences in feeding rate per crab and per feeding claw, feeding duration, and feeding claw size between sexes were studied with the main aim to test male ability to compensate for the loss of one functional feeding claw. Additionally, feeding rate of males and females of small and large size classes was studied. Furthermore, correlations between feeding rate and body size, as well as feeding claw size and body size were investigated. Results showed that increased feeding rate per feeding claw coupled with a larger feeding claw allowed males to compensate for the loss of one feeding claw. Smaller males and females fed faster than larger ones. There was a negative correlation between feeding rate and carapace width. Feeding duration did not vary between males and females of comparable size. A positive correlation was observed between feeding claw size and carapace width.

We investigated the amount of time that large and small, male and female fiddler crabsUca annulipes(H. Milne Edwards, 1837) spent on feeding, walking, standing, grooming, burrowing, inside burrows, fighting, and courtship waving. We video-recorded the activities of 45 males (22 small and 23 large), and 39 females (19 small and 20 large) each for 5 min, and calculated the percentage of time spent on each activity/crab. Our results showed that both sexes spent more time on feeding than on other activities. Males spent more time on building burrows, walking, and grooming than females, and females spent more time inside burrows than males. Smaller males spent more time on feeding, and less time on building burrows and on waving than larger ones. There were no relations between female body size and activities. Feeding rate/feeding claw was higher in males than in females, and crab body size was negatively associated with feeding rate/min.

We studied the population structure ofUca bengaliCrane, 1975 (crab density, sex ratio, and body size (i.e., carapace length and width, major claw length and width)), along with burrow characteristics (diameter, length, depth, and volume) as well as sediment characteristics (percent moisture content and organic matter) along a bank gradient at three distances (2, 4 and 6 m) from the edge of a tidal river. The results showed no differences in crab density, sex ratio, and body size among the three distances. The percent moisture content at 2 m distance was higher than at 4 and 6 m, and the percentage organic matter at 2 m distance was higher than at 6 m distance. Burrows were shorter in length, shallower in depth, and smaller in volume at 2 m distance, but these measures increased with increasing distance from the river edge. Both males and females made three distinct burrow shapes: I, J and U; the J-shaped burrows were the most numerous at all distances.