Multi-Sensor Standalone LoRa System for Early Disaster Prediction

Abstract

In this paper, a self-contained multi-sensor disaster monitoring system consisting of an ESP32 (transmitter) and ESP8266 (receiver) with LoRa SX1278 modules (433 MHz) was implemented to monitor the disaster. The system incorporates flame, temperature, gas (MQ-2), LDR, and rain sensors in order to detect risky conditions within the environment such as fire, gas leakage, overheating and rainfall. The sensor data is digested on pre-defined thresholds and sent in form of structured packets via long range LoRa communication. It has a real-time representation displayed on the receiver, and a buzzer activated when the conditions inside the system are abnormal which means that the system is not dependent on Wi-Fi, GSM and cloud infrastructure and can be used in remote and disaster-proof regions. Experimental findings proof show clear communication with distances of up to 10km, response time-3 to 4 seconds and high detection. The suggested system offers an inexpensive, low energy consuming, and scalable option of early detection of disasters.

Introduction

The text presents a LoRa-based independent disaster monitoring and early warning system designed to detect hazards and reduce loss of life and property. Traditional monitoring systems depend on Wi-Fi, GSM, or internet networks, which may fail during emergencies or are unavailable in remote locations. The proposed system uses LoRa (Long Range Radio) technology because of its long communication range, low power consumption, and reliable operation without external infrastructure.

The system consists of two main nodes:

• ESP32 transmitter node: Collects data from multiple sensors, including flame, gas (MQ-2), temperature (DHT22), rain, and LDR sensors. Sensor values are compared with predefined safety thresholds and transmitted using the SX1278 LoRa module at 433 MHz.
• ESP8266 receiver node: Receives LoRa data, displays real-time information, and activates alerts such as buzzers when abnormal conditions are detected.

The proposed system does not require Wi-Fi, GSM, internet, SIM cards, or LoRaWAN gateways, making it suitable for rural areas, forests, factories, and disaster-prone regions.

Literature Review:

Previous studies have demonstrated that LoRa technology is effective for environmental monitoring due to:

• Long-range communication capability.
• Low energy consumption.
• Reliable operation in areas with limited infrastructure.
• Suitability for applications such as air quality monitoring, weather monitoring, wildfire detection, and agricultural monitoring.

Research has shown that LoRa-based systems provide stable communication even in remote areas, with factors such as RSSI, signal strength, obstacles, and environmental conditions affecting performance.

Methodology:

The proposed system continuously monitors environmental parameters and sends real-time hazard alerts using an ESP32–SX1278 LoRa transmitter and ESP8266 receiver architecture.

The working process includes:

1. Sensor initialization and data collection.
2. Comparison of sensor readings with safety thresholds.
3. Validation of abnormal events to reduce false alarms.
4. Formation of a data packet containing temperature, gas level, flame status, rain status, LDR value, and event time.
5. Long-range transmission through LoRa.
6. Data processing, display, and alarm activation at the receiver.

The system supports multiple sensor nodes, allowing scalable monitoring over large areas.

Advantages of the Proposed System:

• Communication range up to 10 km in open environments.
• Works independently without internet or mobile networks.
• Low power consumption suitable for continuous operation.
• Multi-sensor capability for detecting different hazards.
• Low-cost and expandable architecture.
• Reliable communication using LoRa chirp spread spectrum technology.

Experimental Results:

The prototype was tested using simulated hazards such as:

• Fire detection using flame sensors.
• Gas leakage using butane.
• Temperature changes using a heat source.
• Rain detection using water droplets.
• Light variation using LDR sensors.

Performance evaluation showed:

• Communication range: up to 10 km.
• Packet Delivery Ratio (PDR): 91–95%.
• Response time: 3–4 seconds.
• Power consumption:
  • Transmitter: 60–80 mA
  • Receiver: 40–60 mA
• Detection accuracy: approximately 96%.
• Successful reception of 942 out of 1000 packets.

Conclusion

A standalone LoRa-based multi-sensor disaster monitoring system has been successfully developed and tested. The system provides reliable long-range communication, real-time hazard detection, and low power operation without relying on external networks. Experimental results confirm high detection accuracy, low response time, and stable performance in remote environments. The proposed system is cost-effective and suitable for applications such as forest monitoring, industrial safety, and rural disaster management.

References

[1] E. Twahirwa, K. Mtonga, D. Ngabo, and S. Kumaran, “A LoRa Enabled IoT-Based Air Quality Monitoring System for Smart City,” in Proceedings of the IEEE World AI IoT Congress (AIIoT), 2021. [2] M. F. Abd Rahman, M. H. Husin, and M. F. M. Salleh, “Analysis of Propagation Link for Remote Weather Monitoring System through LoRa Gateway,” in International Journal of Wireless Communication and IoT Systems. [3] S. Gunti, M. P. Reddy, and P. V. Reddy, “Deploying LoRa Technology to Enhance Weather Monitoring System,” in International Conference on Internet of Things and Smart Systems. [4] J. Nyabel, R. Baguma, and D. Musiimenta, “Design and Implementation of a Low-Cost LoRa-Based Sensor Node for Environmental Monitoring in Uganda,” in International Conference on ICT for Development. [5] A. Chara, M. Boulmalf, and H. Harroud, “Efficient Indoor RSSI Analysis for IoT-Based Weather Stations Using LoRa Protocol in Agricultural Applications,” in Journal of Wireless Sensor Networks. [6] S. Munasinghe, A. Jayasena, and T. Wickramasinghe, “FireWatch: LoRa-Based Wildfire Detection and Alert System,” in International Conference on Smart Environmental Monitoring Systems. [7] Y. Zhang, H. Li, and J. Wang, “Long-Distance Environmental Monitoring System Based on Low-Power IoT Technology,” in International Journal of Internet of Things. [8] E. Twahirwa, K. Mtonga, D. Ngabo, and S. Kumaran, “A LoRa Enabled IoT-Based Air Quality Monitoring System for Smart City,” in Proceedings of the IEEE World AI IoT Congress (AIIoT), 2021. [9] M. F. Abd Rahman, M. H. Husin, and M. F. M. Salleh, “Analysis of Propagation Link for Remote Weather Monitoring System through LoRa Gateway,” in International Journal of Wireless Communication and IoT Systems. [10] S. Gunti, M. P. Reddy, and P. V. Reddy, “Deploying LoRa Technology to Enhance Weather Monitoring System,” in International Conference on Internet of Things and Smart Systems. [11] J. Nyabel, R. Baguma, and D. Musiimenta, “Design and Implementation of a Low-Cost LoRa-Based Sensor Node for Environmental Monitoring in Uganda,” in International Conference on ICT for Development. [12] A. Chara, M. Boulmalf, and H. Harroud, “Efficient Indoor RSSI Analysis for IoT-Based Weather Stations Using LoRa Protocol in Agricultural Applications,” in Journal of Wireless Sensor Networks. [13] S. Munasinghe, A. Jayasena, and T. Wickramasinghe, “FireWatch: LoRa-Based Wildfire Detection and Alert System,” in International Conference on Smart Environmental Monitoring Systems. [14] Y. Zhang, H. Li, and J. Wang, “Long-Distance Environmental Monitoring System Based on Low-Power IoT Technology,” in International Journal of Internet of Things.

Copyright

Copyright © 2026 Bhaven V. Peddi, Pushpraj R. Patil, Pushpak N. Phalak, Milind Patil. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.