This project presents a Carbon Capture Air Purifier with Integrated Public Safety Monitoring, designed to enhance indoor air quality while ensuring real-time safety surveillance. The system uses an Electrostatic Precipitator (ESP) to remove airborne carbon particles and dust. The ESP section includes a high-voltage transformer, collector electrodes, and a vibration mechanism for dust removal. A Raspberry Pi 3B+ serves as the central processing unit, interfacing with multiple sensors and communication modules. Environmental parameters—temperature, humidity (DHT11), and air quality (MQ-135)—are continuously monitored and uploaded to the ThingSpeak cloud platform for data analysis and remote access. A microphone module enables audio-based safety detection. The system intelligently recognizes fire-related sounds, screams, and “help” keywords, triggering an emergency response. In any of these scenarios, the Raspberry Pi activates a 360-degree camera to record a 30-second video, which is immediately sent to the administrator via email for rapid intervention. For theft or unauthorized tampering, a vibration sensor detects abnormal movement and similarly initiates automated emergency video capture and email alerting. An LCD display locally shows system status, environmental readings, and alert conditions. A stepper motor allows camera rotation for comprehensive monitoring. By combining air purification, environmental monitoring, audio-based emergency detection, and real-time alerting, this system functions as both a smart air purification unit and a public safety device. It offers an efficient solution for homes, offices, and public places requiring continuous air quality management along with proactive surveillance and emergency response.

          Objectives:

• To design an intelligent air purification system using an Electrostatic Precipitator (ESP) for effective carbon and dust particle capture.
• To continuously monitor environmental parameters such as air quality, temperature, and humidity using IoT-based sensors.
• To detect emergency situations like fire alarm sounds, screams, and “help” keywords through real-time audio analysis.
• To ensure security and theft prevention by using a vibration sensor to detect tampering or unauthorized movement.
• To automatically record and store a 30-second video during any safety-related event using a 360° camera.
• To send instant alerts and evidence (video recording) to the administrator via email for rapid response.
• To upload sensor data to the cloud (ThingSpeak) for remote monitoring, data visualization, and analytics.
• To display real-time system status and environmental readings on an LCD screen for local monitoring.
• To integrate air purification, safety detection, and IoT monitoring into a single compact, cost-efficient, and user-friendly system.
• To enhance indoor safety and air quality through automated, intelligent, and proactive monitoring mechanisms.

          The major building blocks of this project are:

1. Power supply.
2. Raspberry pi3 B+.
3. DHT11 sensor.
4. Mq-135.
5. Vibration motor.
6. MIC
7. LCD display.
8. Stepper motor.
9. Camera
10. Electrostatic Precipitator.

      Software’s used in the project:  

1. Raspbian OS.
2. Express SCH for Circuit Design.
3. THINGSPEAK CLOUD.

Block Diagram :

video: