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This study proposed a system that compares the ESP32Lr-201 board with the Arduino Pro Mini board to determine which is more effective to use. Both of these sensors are based on the Internet of Things (IoT) and use Low Power Wide Area Networks (LPWAN) Long Range (LoRa) as the communication medium. In this study, the LoRa transmission parameters used the frequency of 922.4 MHz, the bandwidth was 125 kHz, a spreading factor was 10, and a code rate was 5. This research compared QoS consisting of delay, throughput, packet loss, Signal Noise Ratio (SNR), and Received Signal Strength Indicator (RSSI) on both the ESP32Lr-201 board and the Arduino Pro Mini board. Board and change the analog value use the YL-38 Analog-Digital Converter (ADC) sensor. The datasheet in this study helped facilitate calibration and data conversion in the manufacture of digital NPK sensors. These sensors later facilitated the data collection of nitrogen (N), phosphorus (P), and potassium (K) contained in the soil to control soil and soil levels. This way, fertilization can be more effective. The DHT 11 sensor in the Application and Technology Platform as your Reliable Solution (ANTARES) Shield has added a feature to monitor temperature and humidity in the room. The study’s data collection was carried out at 5 points and their distance from the gate of Sentral Telepon Otomat (STO) Tarungga Bandung, Indonesia, ranges from 1.1 Km to 8.4 Km. From the extensive measurement, it was found that the ESP 32 was more effective than the Arduino Pro Mini in terms of Quality of Service (QoS). [ABSTRACT FROM AUTHOR]

According to data from the Earth's Volcano and Geological Disaster Reduction Center, a country like Indonesia has experienced many natural disasters, one of which is flooding. Floods are an annual natural disaster, especially on mountain slopes. Mountainous areas experience more dangerous than floods than the urban areas because they can cause other natural disasters, such as landslides and damage the hiking trails. The steep and winding roads minimize and limit the number of officers working in the mountains. Therefore, flood detection and monitoring equipment is needed. The proposed system based on AIoT technology provides real-time flood analysis so that the authorities can monitor residents around mountainous areas and provide early warning. This research focuses on the flood observation system as an early warning system to effectively monitor the flood-prone mountain slopes in real time while taking into account the cost, time efficiency, and safety measurement. The proposed system design includes the integration of sensors into the microcontroller, and the communication between the posts using LoRa and SIM900 sends data to the cloud server via the Internet. All sensor readings for each post are displayed on the app, and alerts are sent via SMS and the app. [ABSTRACT FROM AUTHOR]

A Plant Microbial Fuel Cell (Plant-MFCs) has been studied both in the lab and in a field. So far, field studies were limited to a more conventional Plant-MFC design, which submerges the anode in the soil and places the cathode above the soil surface. However, for a large scale application a tubular Plant-MFC is considered more practical since it needs no topsoil excavation. In this study, 1 m length tubular design Plant-MFC was installed in triplicate in a paddy field located in West Kalimantan, Indonesia. The Plant-MFC reactors were operated for four growing seasons. The rice paddy was grown in a standard cultivation process without any additional treatment due to the reactor instalation. An online data acquisition using LoRa technology was developed to investigate the performance of the tubular Plant-MFC over the final whole rice paddy growing season. Overall, the four crop seasons, the Plant-MFC installation did not show a complete detrimental negative effect on rice paddy growth. Based on continuous data analysis during the fourth crop season, a continuous electricity generation was achieved during a wet period in the crop season. Electricity generation dynamics were observed before, during and after the wet periods that were explained by paddy field management. A maximum daily average density from the triplicate Plant-MFCs reached 9.6 mW/m 2 plant growth area. In one crop season, 9.5-15 Wh/m 2 electricity can be continuously generated at an average of 0.4 ± 0.1 mW per meter tube. The Plant-MFC also shows a potential to be used as a bio sensor, e.g., rain event indicator, during a dry period between the crop seasons.