Modernizing the Internet of Things in Islamic boarding schools is essential to eliminate backwardness and skills gaps. Santri must have cognitive, affective, psychomotor, and creative intelligence to be ready to enter the industrial and business world. The students’ need for information transparency can be resolved using technology. This is because the empowerment of the Internet of Things has become a separate part of Islamic boarding school activities with students who can connect in real-time. This research aims to analyze current conditions and stakeholder involvement regarding the application of the Internet of Things in innovative Islamic boarding school services in the era of disruption. The Descriptive Method and Individual Interest Matrix Analysis were used by involving 130 respondents from the internal environment of the Daarul Rahman Islamic boarding school and completing the questionnaire through FGD (Focus Group Discussion) with the leaders of the Daarul Rahman Islamic boarding school. The results show that the current condition of Islamic boarding schools is that most need to learn or understand IoT, even though they are enthusiastic about learning new things and flexible in accepting change. The challenges required in implementing IoT are financial investment, increasing human resources through training, and synergy between Islamic boarding school policy makers. Mutually supportive and solid conditions are required between foundations, school principals, and school committees to implement IoT at Daarul Rahman Islamic Boarding School. Collaboration with various parties is needed because the implementation of IoT cannot be done alone by Islamic boarding schools but with the support of various related parties.

The rapid development of cities and urbanization in China has forced the growth of new channels for buying agricultural products. The purpose of this research is to examine how Internet of Things (IoT’s) technologies can digitize a traditional fresh food supply chain. Comparative and descriptive analysis methods are used to highlight the major pain points in the traditional supply chains and assess how digital transformation could help. We delve into every part of digital transformation, which includes establishing an information platform based on IoT and developing smart storage options. Our findings revealed that through end-to-end digital integration, supply chain efficiency is improved with shorter lead times and leaner inventories that yield reduced costs as well as fewer losses while ensuring product quality and traceability. In sum, such an approach would enhance sustainability within the fresh food value chain. As such, our article highlights key aspects of transitioning towards a digital environment in this sector for those planning similar ventures.

The growth of mobile Internet has facilitated access to information by minimizing geographical barriers. For this reason, this paper forecasts the number of users, incomes, and traffic for operators with the most significant penetration in the mobile internet market in Colombia to analyze their market growth. For the forecast, the convolutional neural network (CNN) technique is used, combined with the recurrent neural network (RNN), long short-term memory network (LSTM), and gated recurrent unit (GRU) techniques. The CNN training data corresponds to the last twelve years. The results currently show a high concentration in the market since a company has a large part of the market; however, the forecasts show a decrease in its users and revenues and the growth of part of the competition. It is also concluded that the technique with the most precision in the forecasts is CNN-GRU.

This study delves into the evolving landscape of smart city development in Kazakhstan, a domain gaining increasing relevance in the context of urban modernization and digital transformation. The research is anchored in the quest to understand how specific technological factors influence the formation of smart cities within the region. To this end, the study adopts a Spatial Autoregressive Model (SAR) as its core analytical tool, leveraging data on server density, cloud service usage, and electronic invoicing practices across various Kazakhstani cities. The crux of the research revolves around assessing the impact of these selected technological variables on the smart city development process. The SAR model’s application facilitates a nuanced understanding of the spatial dynamics at play, offering insights into how these factors vary in influence across different urban areas. A key finding of this investigation is the significant positive correlation between the adoption of electronic invoicing and smart city development, a result that stands in contrast to the relatively insignificant impact of server density and cloud service usage. The conclusion drawn from these findings underscores the pivotal role of digital administrative processes, particularly electronic invoicing, in driving the smart city agenda in Kazakhstan. This insight not only contributes to the academic discourse on smart cities but also holds practical implications for policymakers and urban planners. It suggests a strategic shift towards prioritizing digital administrative innovations over mere infrastructural or technological upgrades. The study’s outcomes are poised to guide future smart city initiatives in Kazakhstan and offer a reference point for similar emerging economies embarking on their smart city journeys.