The latest innovations, such as the use of artificial intelligence and machine learning algorithms to improve fire detection accuracy and minimize false alarms.
PROJECT Fire Detection and Alarm Circuit Report .docx
PROJECT Fire Detection and Alarm Circuit Report .docx
1. Fire Detection and Alarm Circuit
PROJECT
ABSTRACT
The latest innovations, such as the use of artificial
intelligence and machine learning algorithms to
improve fire detection accuracy and minimize false
alarms.
Submitted To
Md.Sohel Rana
Lecturer
Department of Electrical and
Electronic Engineering
Submitted By
Md Meshkat Hasan (213-33-1455)
Md Asif Hossain (213-33-1409)
Md Fahim Tasnim Akanda (213-33-1426)
Khalid Saifullah (213-33-1432)
Md Manik Hossain (213-33-1434)
Department of Electrical and Electronic
Engineering
Md.Mubassir Sajid (213-33-1407)
2. Project Name: Fire Detection and Alarm Circuit
Objective: The objective of a fire detection and alarm circuit is to
provide an early warning system for detecting the presence of fire or
smoke and alerting occupants or relevant authorities to take appropriate
actions. Thereby minimizing potential damage and ensuring the safety of
individuals in the protected area.
Theory: A fire detection and alarm circuit is a system designed to detect
the presence of fire or smoke in a protected area and provide early
warning through audible and visual alarms. The circuit utilizes various
components and follows a specific theory of operation.Smoke detectors
use optical or ionization methods to detect smoke particles in the air.
Heat detectors sense rapid temperature increases in the environment.
They can be either fixed temperature detectors, which trigger an alarm
when a predetermined temperature threshold is reached, or rate-of-rise
detectors, which detect a rapid temperature increase within a short
period. When the control panel determines the presence of a fire, it
triggers the activation of alarm devices. These devices can include
audible alarms such as sirens, horns, or bells to alert occupants in the
area. Visual indicators such as strobe lights or flashing lights are also used
to provide visual alerts, especially for individuals with hearing
impairments.
Apparatus Required:
1. UA741 OP-AMP
2. IC Base 8 Pin
3. Resistor (100K 1/4W)
4. VEROBOARD
5. LED Red
6. Cables and Connectors
7. Active Buzzer
3. 8. Battery
9. IR Receiver (5mm)
Circuit Diagram:
Working Procedure: Place the UA741 op-amp on the IC base or
directly on the Veroboard/breadboard. Connect Pin 2 of the UA741 op-
amp to the positive rail of the power supply (battery) using a cable or
wire. Connect Pin 4 of the UA741 op-amp to the negative rail (ground) of
the power supply. Connect Pin 3 of the UA741 op-amp to the negative
rail using a resistor (100K). Connect the other end of the resistor to Pin 2
of the UA741 op-amp. Connect Pin 6 of the UA741 op-amp to the positive
rail through a suitable current-limiting resistor (e.g., 220-470 ohms).
Connect the anode (longer leg) of the red LED to Pin 6 of the UA741 op-
amp and the cathode (shorter leg) to the negative rail. Connect the
positive terminal of the active buzzer to Pin 6 of the UA741 op-amp and
the negative terminal to the negative rail. Optionally, connect the IR
receiver to Pin 5 of the UA741 op-amp for additional fire detection
capabilities. Connect the positive and negative terminals Ensure that all
connections are secure and connections of the power supply (battery) to
the respective rails on the Veroboard/breadboard. Activate the circuit
and observe the behavior of the LED and active buzzer. If using an IR
receiver, test its functionality by directing a suitable IR source towards it.
LM741
4. Discussion: The primary goal of a fire detection and alarm circuit is
to detect fires at the earliest possible stage. It provides an audible and
visual signal that prompts individuals to evacuate the area immediately.
Engage in a discussion about the effectiveness of alarms in capturing
people's attention and ensuring a swift response. The latest
innovations, such as the use of artificial intelligence and machine
learning algorithms to improve fire detection accuracy and minimize
false alarms.