LoRa & IoT Based Automatic Disaster Monitoring & Alert System

Abstract

In times of natural and industrial disasters, quick detection and reliable communication are essential to minimize damage and save lives. The proposed LoRa and IoT-based Automatic Disaster Monitoring and Alert System provides an efficient, low-cost, and long-range solution for real-time disaster management. The system integrates various sensors to monitor parameters such as earthquake vibrations, gas leaks, flood levels, temperature, humidity, and human occupancy. Sensor data is collected by a NodeMCU (ESP8266) and transmitted through LoRa communication to a base station for further processing and cloud upload via platforms like ThingSpeak or Ubidots. In critical conditions, the system triggers automatic alerts through GSM modules (SMS/calls) and local alarms, ensuring communication even during internet failures. Additional features such as automatic door control and people counting enhance safety and assist rescue operations. The system operates efficiently with low power consumption and solar backup, making it suitable for remote and disaster-prone areas. This project demonstrates a scalable, energy-efficient, and internet-independent approach to disaster monitoring, offering early warnings, reliable alerts, and enhanced safety for communities, industries, and public infrastructures.

Introduction

The LoRa-IoT Based Disaster Monitoring and Alert System is an intelligent early-warning solution designed to enhance emergency response and communication during disasters such as earthquakes, floods, and gas leaks. It integrates LoRa (Long Range communication) technology with IoT cloud platforms and GSM alerts, ensuring reliable operation even when internet connectivity fails.

Objective

To provide real-time monitoring, automatic alerting, and local automation during disasters through a dual-path communication system that functions both online (IoT cloud) and offline (LoRa + GSM).

Key Features

• LoRa Communication: Enables long-range, low-power data transmission between remote sensors and the base station (up to 10 km).

• IoT Cloud Integration: Stores and visualizes sensor data on platforms like ThingSpeak or Ubidots for remote access.

• GSM Alerts: Sends instant SMS/call notifications to authorities or residents when critical thresholds are reached.

• Automatic Safety Control: Activates motorized door closure during emergencies to secure bunkers or shelters.

• People Counting: IR-based system tracks occupancy, aiding rescue teams in locating trapped individuals.

• Solar-Powered Backup: Ensures continuous system function during power outages.

Disaster Modules

• Earthquake: Detects ground vibrations and sends instant alerts; inspired by real-world events such as the 2015 Gorkha earthquake.

• Flood: Monitors water levels and rainfall using ultrasonic and humidity sensors; responds to cases like the 2019 Kolhapur–Sangli floods.

• Gas Leak: Identifies toxic gas emissions using MQ sensors; references major incidents such as the 1984 Bhopal and 2020 Vizag gas leaks.

Methodology

1. Sensor Deployment: Nodes with vibration, gas, ultrasonic, temperature, humidity, and IR sensors are installed in vulnerable areas.

2. Data Collection (Field Side): NodeMCU (ESP8266) gathers readings and transmits them through the LoRa transmitter.

3. Data Reception (Base Station): Another NodeMCU with LoRa receiver collects data, filters noise, and uploads it to the cloud.

4. Disaster Detection: Predefined thresholds trigger alarms for flood, earthquake, or gas leak events.

5. Alert Generation: The GSM module sends automatic SMS/calls, while buzzers or voice alarms warn nearby individuals.

6. Automatic Response: Motorized door closes automatically; occupancy data assists rescue operations.

7. Monitoring Interface: A dashboard displays real-time data, alert history, and system health.

Literature Support

Research from 2023–2025 demonstrates the potential of IoT and LoRa in early disaster management, human detection, and occupancy monitoring. The proposed system advances these ideas by combining LoRa communication, GSM alerts, and automation in one integrated framework.

Future Scope

1. AI & Machine Learning: For predictive disaster modeling and anomaly detection.

2. Drone Integration: For aerial surveillance and remote area assistance during emergencies.

Conclusion

The LoRa and IoT-based automatic disaster monitoring and alert system provides a reliable, low-cost, and efficient solution for disaster management. By integrating various sensors with NodeMCU, LoRa communication, and IoT cloud platforms, the system ensures real-time monitoring of earthquakes, floods, gas leaks, and environmental conditions. The dual alert mechanism using IoT dashboards and GSM fallback guarantees continuous communication even during internet failures. Features like automatic door control and people counting enhance safety and support rescue operations. Overall, this project demonstrates a scalable and energy-efficient approach to disaster preparedness, capable of saving lives and minimizing damage during emergencies.

References

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Copyright

Copyright © 2025 Mr. Shailesh Ashok Shinde, Ms. Anushka Shital Bhavare, Ms. Shravani Janardan Ambi, Ms. Sanchita Parashram Ambi, Ms. Sanskruti Amol Admuthe. 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.