DEVELOPMENT AND IMPLEMENTATION OF DATA COMPRESSION TECHNIQUE FOR IOT SENSOR DATA TRANSMISSION IN AQUACULTURE ISOLATED FROM INTERNET NETWORK THROUGH LORAWAN GATEWAY ANTARES TELKOM

• Main Author: Ahmad Khaderani, Helmi
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/85104
• Institution: Institut Teknologi Bandung

Aquaculture in isolated areas often challenges in terms of monitoring and management due to limited internet network access. In an effort to solve this problem, the research was conducted by developing and implementing a LoRa- based IoT communication system. The communication system is expected to be able to transmit sensor data efficiently and reliably in areas with limited internet network access. This system consists of LoRa RFM95W module and ESP32 microcontroller. The system also uses a backhaul connection in LoRaWAN gateway Antares Telkom. The selection of the LoRa RFM95W module is based on its ability to operate in the 920-923 MHz frequency band in accordance with Indonesian regulations. This module offers long-range communication with low power consumption. In LoRa class settings, the author chose class A because of the power efficiency it offers. Devices in class A are only active when sending or receiving data, so they can save battery life significantly. This is especially important for IoT devices that often have to operate for long periods of time without frequent charging. One important technical aspect in the use of LoRa is the selection of the Spreading Factor (SF). A higher SF extends the airtime for each data transmission, which in turn increases the communication range. However, it also slows down the data rate. Therefore, SF selection should be adjusted according to application needs and operational environment conditions to achieve a balance between range, data rate, and power consumption. This research also includes the development of data compression techniques that aim to minimize data loss during the compression and decompression process, as well as reduce the size of transmitted data without compromising quality and accuracy. These techniques are important for optimizing bandwidth usage and ensuring accurate and real-time data integration. In addition, this system also provides a backup mechanism for decompressed data to ensure data reliability. There are 2 types of tests carried out, namely data transmission testing with variations in compression algorithms and data transmission testing with variations in distance. Data transmission with compression algorithms is conducted to find the best compression algorithm with the largest compression ratio. From this experiment, it was found that the unishox2 compression algorithm can send data up to 347 bytes with a compression ratio of more than 1. Data transmission testing with distance variations was carried out with the best compression algorithm, namely unishox2. Tests with distance variations obtained by sending with SF9 parameters get low signal loss with data sizes that can be sent up to 347 bytes.