DEVELOPMENT OF A WEB DASHBOARD FOR MONITORING AQUACULTURE ENVIRONMENTAL CONDITIONS ISOLATED FROM THE INTERNET NETWORK USING LORA MODULE DATA TRANSMISSION

• Main Author: Shafly Nurrasyid, Muhammad
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/85109
• Institution: Institut Teknologi Bandung

This research develops a web dashboard to monitor environmental conditions in aquaculture isolated from the internet network, using LoRa modules for data transmission. The main challenge in managing aquaculture in remote areas is limited internet access, which hinders data transmission from IoT sensor networks to servers. LoRa was chosen as a solution due to its capability to transmit data over long distances with low power consumption, making it an ideal choice for data transmission in areas that are difficult to reach with internet networks. In the implementation, IoT sensors monitoring various environmental parameters, such as water temperature, pH, and oxygen levels, are connected to LoRa modules via ESP32 microcontrollers. Data collected by the sensors is transmitted via the LoRa network to a LoRaWAN gateway, which connects to an IP-based network. From this gateway, data is forwarded and stored on servers provided by LoRa service providers, such as Antares Telkom. This data is then accessed by the developed web dashboard, allowing aquaculture managers to monitor environmental conditions in real-time and make better decisions. Frontend development of the web dashboard was developed using HTML for structuring the web page, while CSS and Bootstrap were used for visual styling to make the dashboard more attractive. JavaScript was employed to enhance interactivity, making the web page more responsive. On the backend, Flask framework was used to handle web application logic and provide APIs for processing requests from the frontend. MySQL as database management system was used for data storage, with SQLAlchemy facilitating communication between Flask and MySQL. Data from IoT sensors stored on the Antares server is accessed through integration between Flask backend and Antares API. This data is then decompressed using the Unishox2 library before being stored in MySQL. Analysis of user interface testing shows that the frontend design received a high Likert scale index value, with an average score above 87%. This indicates ease of navigation on dashboard, clarity of information presented by data, fast data loading on dashboard, and suitability of dashboard for monitoring IoT sensor data. On the backend, performance testing of the web dashboard shows that all menus, iv submenus, and features function with a response time ranging from 30 ms to 133 ms. The highest response times were due to fetching and checking data from the database and displaying sensor data graphs. Despite this, response times remain acceptable for data monitoring web applications. Backend testing also confirmed that data from Antares is successfully backed up and automatically stored in the MySQL database each time the dashboard is accessed by a user.