The main controlling device of the project is the Raspberry Pi processor, which acts as the brain of the system. A Pi Camera, GPS module, four sound sensors, and DC motors interfaced through an L293D motor driver are connected to the Raspberry Pi. When the sound sensors detect any abnormal or suspicious sound, the signals are processed by the Raspberry Pi, which determines the direction of the sound source. Based on this analysis, the Raspberry Pi controls the motor driver to move the robot towards the detected sound. Once the robot approaches the source, the Pi Camera is activated to begin real-time video streaming. The captured video is transmitted via Wi-Fi and sent to a registered email ID for remote monitoring. Simultaneously, the GPS module provides the exact location coordinates, which are also shared along with the video feed to enhance situational awareness. In addition to sound-based tracking, the system can incorporate a PIR sensor for motion detection and an ultrasonic sensor for obstacle avoidance, ensuring smooth and safe navigation. A GSM module can also be used to send SMS alerts in case of critical events. The robot is powered by a battery system regulated through an LM2596 voltage converter, ensuring stable and efficient operation. The system also includes a buzzer for immediate alerts, headlights for visibility in low-light conditions, and LED indicators for status display. This integrated system enables effective night-time surveillance with real-time monitoring, quick response, and enhanced security.      

Objectives:

• To develop a smart surveillance robot using a Raspberry Pi.
• To detect suspicious sounds and automatically move towards the sound source.
• To capture and stream live video using a Pi Camera.
• To track and share the robot's location using a GPS module.
• To avoid obstacles using an ultrasonic sensor for safe navigation.
• To detect human movement using a PIR sensor.
• To send emergency alerts through a GSM module and email.
• To provide efficient night-time security with real-time monitoring.

          The Major building blocks of this project are:

• Raspberry pi zero w 2.
• Battery.
• DC motor with driver.
• Four sound sensors.
• Pi camera.
• GPS.
• Rechargeable Battery.
• LED indications.
• GSM.
• PIR sensor.
• Ultrasonic sensor.
• Buzzer.
• Head Lights.

        Software’s used:    

1. Python programming.
2. Raspbian OS.
3. Express SCH for Circuit design.

         

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