Integrating Autonomous Line Following Model using PID Controller with Enhancing Location Intelligence

It presents Autonomous Line Following Model, leveraging the transformative capabilities of Internet of Things (IoT) technology. The integration of real-time object detection ensures dynamic tracking of surrounding objects, while precision lane following guarantees adherence to a predefined path through a Proportional-Integral- Derivative (PID) algorithm. Live monitoring is achieved through Webcam by image processing, Convolution Neural Networks (CNNs), enabling remote access to the vehicle's camera feed. This multifaceted approach not only amplifies location intelligence but also provides high-quality live-streaming capabilities, significantly enhancing the model's real-world applicability. Project provides accident prevention using different sensor simulation whereas the vehicle is stopped slowly and enabling the HRMS watch module enables driver status detecting the heart monitoring function of the driver The synergy of these components underscores the immense potential of IoT in autonomous systems, exemplifying efficient and intelligent navigation.