The development of reliable wireless networks is crucial for advancing sustainability. Not only does it facilitate remote work and telecommunication which are critical remote services such as telemedicine and distance education, they are also essential in supporting sustainable practices like the application of IoT in monitoring environmental conditions and energy usage. To ensure that these networks work optimally, it is essential that the datasets used in their development are not only accurate but are also distinct. This study contributes to this end by analyzing the datasets generated by the COST 2100, a model that is used extensively in wireless communications. Using ANOVA, the researchers determined if the dataset are indeed distinct as signals bounce about multiple clustering which use Multiple Input, Multiple Output (MIMO) Technology similar to modern wireless systems like 5G. Results show that the different variables or dimensions are distinct from each other. Thus, the datasets generated by COST2100 are suitable to be utilized in further preprocessing methods of wireless multipath clustering, ultimately contributing to building a more sustainable wireless communication system.

A sustainable electronics engineering program effectively prepares graduates to tackle the changing technological, environmental, and societal challenges. In this context, this study examines the relationship between Outcome-Based Education (OBE), quality assurance mechanisms, and student performance in the Electronics Engineering Licensure Examination with the goal of enhancing the development of the program and making it more sustainable. To do this, the paper analyzed a five-year dataset to examine key factors such as accreditation by the Philippine Technological Council (PTC), international rankings (QS and THE), and recognition as Centers of Excellence (COE) or Centers of Development (COD) by the Commission on Higher Education (CHED). Regression modeling of the data gathered revealed that the linear interaction model most effectively predicts student performance, with an R-squared value of 0.85, highlighting the emphasis on OBE and quality assurance to improve academic results. The study concluded that emphasizing interactions among program attributes can guide curriculum revisions to enhance student success and ultimately, its sustainability. It suggested that future studies integrate machine learning (ML) techniques to improve the predictive capabilities of model to enhance quality assurance measures. This may be done by utilizing ML methodologies from related fields such as human detection systems and ECG analysis and apply it to educational research. Such an implementation can enhance data-driven decision-making processes, thereby improving the quality of education and student performance in the Electronics Engineering Licensure Examination and ultimately, making the program more sustainable.

The integration of Internet of Things (IoT) technology in the agricultural sector using advanced sensor systems has garnered significant interest in the recent year, especially in promoting food security. This study shows an application of this to Spondias purpurea (Philippine Pias Prunes), an important fruit in the Philippine Archipelago. The developed system places significant importance on the connection of Internet of Things (IoT) devices and the Google Cloud Platform. This integration enables real-time monitoring, data storage, and analysis, therefore providing valuable insights into enhancing the drying process and mitigating spoilage by maintaining moisture levels within the recommended range of 12-14%. The technology provides farmers with the opportunity to extend the shelf life of the prunes, reduce food wastage and increased profitability. While the system focused on Spondias purpurea, the system is highly adaptable and scalable to other fruits and crops. The research employed a DHT11 sensor that is linked to a Raspberry Pi Microcontroller, together with a Google Cloud-Based Platform for the purpose of data storage and processing. Results of the experiments indicate that the temperature measurements remain consistent at varying conditions. Moreover, the humidity levels remain to be high while the prune’s moisture content continue to be steady. To enhance the system's functionality, future endeavours should focus on integrating the system with other agricultural processes. Additionally, it is recommended to broaden the scope of the cost-benefit analysis by considering aspects such as the initial investment, maintenance costs, energy consumption, and potential rewards in terms of product quality, loss reduction, and increased output.

The fast progression of Artificial Intelligence (AI) technology has elicited substantial ethical issues, especially within engineering fields that directly impact society. This study seeks to establish a framework for integrating Ethical AI ideas into engineering curriculum, therefore preparing future engineers to address the moral, social, and legal ramifications of AI. The framework incorporates Ethical AI principles into current course formats, encompassing introductory, enabling, and demonstrative courses, with particular focus on subjects like Science, Technology, and Society, Professional Engineering Ethics, and thesis/capstone projects. The paper recommends a curriculum update that complies with industry norms and equips students to embrace responsible AI practices, based on a thorough analysis of pertinent Commission on Higher Education (CHED) Memorandum Orders (CMOs) and literature. The research also presents evaluation rubrics to gauge students' comprehension and implementation of Ethical AI concepts in their academic projects. The paper suggests that integrating Ethical AI into engineering education enables universities to cultivate engineers who possess both technical proficiency and a robust ethical framework about AI technology.

Due to the hardships brought about by the pandemic, Filipino farmers resort to creative ways of drying fruits. Since there is limited movement during the pandemic brought about by restrictions, farmers have no choice but to employ fruit drying on the roof of their houses to preserve the food. Currently, this is done at the mercy of the elements. However, modern fruit-drying requires monitoring of temperature and humidity so that proper measures can be taken when it is about to rain. Otherwise, rain can cause food spoilage which would cause farmer’s wastage of already scarce resources. The crop chosen for this study was Spondias sp. However, a minor adjustment can also be applied to other fruits, vegetables, and even meat. Once the drying process is complete, the farmer will receive a notification so that the dried product may be processed for packing and selling. Results indicate that the prototype can meet the specifications and that farmers found it helpful. For future works, it is recommended that solar panels be used to utilize the power from the sun. It is also recommended that direct current be used in future project modifications to minimize errors during a power outage.