Fire Alarm System Project

Abstract

The Fire Alarm System Project is a safety-focused automation system designed to detect fire hazards using temperature and/or flame sensors. When a potential fire is detected, the system activates an audible and visual alarm to alert nearby individuals. It is a cost-effective, real-time monitoring solution suitable for homes, offices, industries, and schools. This project emphasizes early fire detection and quick response using microcontrollers and sensors.

Objectives

• Detect fire using a flame sensor, smoke sensor (MQ-2/MQ-135), or temperature sensor (LM35).

• Trigger an alarm (buzzer, LED, or GSM alert) in case of fire detection.

• Build an automatic, reliable, and fast-response safety system.

• Optionally send an SMS alert using GSM module (SIM800L).

Components Used

• Arduino Uno / NodeMCU / Raspberry Pi

• Flame Sensor / IR Flame Sensor

• MQ-2 Gas Sensor / LM35 Temperature Sensor

• Buzzer & LED Indicators

• Relay Module (for fan/water pump)

• GSM Module (optional)

• Breadboard, Jumpers, Power Supply

Working Principle

The system continuously monitors environmental conditions using flame or smoke sensors. When it detects:

• High temperature,

• Presence of flame, or

• Gas/smoke concentration above threshold,
  It activates:

• A buzzer to sound the alarm,

• An LED to signal danger, and

• Optionally, sends a text message to a registered mobile number via GSM.

Methodology

1. Connect flame/gas sensors to analog or digital pins of Arduino.

2. Interface the buzzer and LED to provide alarms.

3. Set threshold values in the Arduino code.

4. Upload the program and power the circuit.

5. Test using a lighter (at a safe distance) or simulated heat/gas to trigger the system.

Applications

• Home fire safety

• School and office fire protection

• Industrial hazard detection

• IoT-based safety systems

Future Scope

• Add Wi-Fi or Bluetooth for real-time alerts on smartphones.

• Integrate a sprinkler system with relay control.

• Expand to large buildings with multi-zone detection.

• Store sensor readings in cloud for data analysis.

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