Assimilation of IoT sensors for Data Visualization in a Smart Campus Environment

Recently, various indoor based sensors that were formerly separated from the digital world, are now intertwined with it. The data visualization may aid in the comprehension of large amounts of information. Building on current server-based models, this study intends to display real environmental data acquired by IoT agents in the interior environment. Sensors attached to Arduino microcontrollers are used to collect environmental data for the smart campus environment, including air temperature, light intensity, and humidity. This proposed framework uses the system's server and stores sensor readings, which are subsequently shown in real time on the server platform and in the environment application. However, most current IoT installations do not make use of the enhanced digital representations of the server and its graphical display capabilities in order to improve interior safety and comfort conditions. The storage of such real-time data in a standard and organized way is still being examined even though sensor data integration with storing capacity server-based models has been studied in academics.

Knowledge Management Model for Smart Campus in Indonesia

The application of smart campuses (SC), especially at higher education institutions (HEI) in Indonesia, is very diverse, and does not yet have standards. As a result, SC practice is spread across various areas in an unstructured and uneven manner. KM is one of the critical components of SC. However, the use of KM to support SC is less clearly discussed. Most implementations and assumptions still consider the latest IT application as the SC component. As such, this study aims to identify the components of the KM model for SC. This study used a systematic literature review (SLR) technique with PRISMA procedures, an analytical hierarchy process, and expert interviews. SLR is used to identify the components of the conceptual model, and AHP is used for model priority component analysis. Interviews were used for validation and model development. The results show that KM, IoT, and big data have the highest trends. Governance, people, and smart education have the highest trends. IT is the highest priority component. The KM model for SC has five main layers grouped in phases of the system cycle. This cycle describes the organization’s intellectual ability to adapt in achieving SC indicators. The knowledge cycle at HEIs focuses on education, research, and community service.

Propuesta de la enseñanza de la inmótica para contribuir con la implementación del Smart Campus de la UNE, Perú.

El desarrollo de la tecnología como la inteligencia artificial, el internet de las cosas (IoT), la ciencia de datos, entre otros, obliga a las universidades a empoderarse en el estudio y manejo de sus contenidos; el objetivo de la propuesta es sugerir un conjunto de contenidos para la enseñanza de la inmótica como contribución a la implementación del Smart Campus en la Universidad Nacional de Educación; el trabajo de investigación permite tener nueva visión desde la tecnología para la protección del medioambiente, la eficiencia energética, la reducción de residuos y molestias, el mejoramiento de la inclusión social que llevará a generar un ecosistema donde infraestructuras, servicios y tecnologías se unen para ofrecer un entorno a medida del hombre.