Claim Missing Document
Check
Articles

Found 12 Documents
Search
Journal : TEPIAN

A Virtual Museums and 3D Artefacts to Improve Cultural Heritage Education Satria, Bagus; Ramadhani, Fajar; Karim, Syafei; Aini, Nur
TEPIAN Vol. 4 No. 4 (2023): December 2023
Publisher : Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tepian.v4i4.2967

Abstract

In the current era of globalization and modernization, the imperative to safeguard and convey cultural heritage and history to society becomes increasingly significant. Web-based virtual museums have emerged as a pivotal solution, facilitating the preservation and promotion of cultural heritage on a global scale. These virtual platforms offer visitors unprecedented access to artifact collections, transcending the limitations of physical museum visits. The immersive features, such as the ability to view objects from diverse angles and zoom in on intricate details, present a profound and engaging experience. This research is to contribute insights into the development of effective web-based virtual museums featuring 3D artifact representations, thereby making a meaningful contribution to the broader field of cultural heritage preservation. The primary objective of this study is to enrich the exploration and learning experiences of visitors in the realm of cultural heritage through digital platforms. The research employs a structured software development methodology encompassing vital stages like needs analysis, system design, implementation, testing, and maintenance. By focusing on the technological aspects, the study seeks to address challenges related to quality and reliability faced by web-based virtual museums. Furthermore, the findings aim to enhance the overall effectiveness of these museums in offering a comprehensive and captivating journey through cultural artifacts. This research is poised to not only advance the field of virtual museum development but also foster a deeper appreciation and understanding of our rich cultural heritage.
Cloud Storage for Object Detection using ESP32-CAM Imron, Imron; Satria, Bagus; Karim, Syafei; Ramadhani, Fajar
TEPIAN Vol. 5 No. 2 (2024): June 2024
Publisher : Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tepian.v5i2.2994

Abstract

Cloud storage services can create an object storage bucket to store our pictures, among them the Cloud Storage FUSE, Scaleway, S3 bucket, Firebase,  etc. intelligent IoT systems generate vast amounts of multi-source industrial data, which necessitate a large amount of storage and processing power to enable real-time data processing and analysis. Cloud computing can be intricately linked into intelligent IIoT systems due to its strong computational and storage capabilities. Cloud Storage for Object Detection using ESP32-CAM. Create a workable solution that supports distributed storage bucket and implement it in a real-world setting. Implement the entire system as an addition to the well-known IoT cloud storage and run multiple experiments to evaluate its functionality in scenarios with varying setups and system. The target objects that are used as data sets are the ESP8266, Wemos D1, and Arduino Uno. Figuring out the ideal parameters for training the FOMO (First Object, More Object) model and then putting it into practice. It was necessary to find a balance between learning rate and accuracy, on the other hand, to maintain the highest possible accuracy in the identification of the microcontroller object to minimise the number of false positive reports. Find the value learning rate effective to this object is 0.01 with F1 score 98.7% and accuracy score 89.58%.