Magazine Identification on SS1-V1 Assault Rifle using Web-based HX711 Load Cell Sensor
Main Article Content
Abstract
The SS1-V1 is an assault rifle model equipped with a magazine as one of its main components. The magazine plays a crucial role in storing and loading ammunition. However, magazines must be stored separately from the weapon as their integrated storage can pose a risk to a country’s security. Therefore, this research proposes a web-based system capable of identifying the presence of magazines in weapons in real-time. This system is supported by various hardware components, including a load cell sensor, HX711 sensor module, Arduino UNO R3, and an Ethernet shield for network connectivity. In addition, API is used for data management, which is then stored in the database. The results of this research indicate that the average response time for each rack within a cabinet is between 2.7s to 3.3s, while for racks serving as slaves, it ranges from 14.16s to 15.01s. Based on the results of the weight-based weapon identification testing, there is a weight difference of 0.1kg to 0.2kg. These results state that all tests were successfully identified by the web system according to the conditions of the weapons on the rack.
Downloads
Article Details
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work