The objective of this paper is to present an effective and reliable method for the traffic surveillance using the concepts of digital image processing. The paper proposes a system that can detect, track, and estimate velocity of vehicles using an uncalibrated camera and also detect and recognize their registration number plate. This approach provides a cost-effective alternative for traffic flow monitoring and surveillance. This robust system finds its applications in urban traffic management systems, military installation, and research facility security systems. This approach is a computationally efficient approach for detecting and tracking moving cars on the road utilizing uncalibrated cameras mounted on the road. It is also helpful for military installation because all the security issues have been detected by using this approach.

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The covid-19 virus has been linked to an acute outbreak of the disease that has passed for years. Clear explanations of these should be provided by trained professionals and those with healthcare experience who have the energy to work on intensive care. The World Health Organization (WHO) has taken various steps to address this. These can be audited by NETCCN (National Emergency Telecritical Care Network) using digital technology. This section explains a lot. It is proposed by the National Emergency Telecritical Care Network (NETCCN). This digital health information will be solved as an updated version 2.0, which will greatly improve future emergencies. The proposed method of digital predication support for Artificial Intelligent (AI). Use these to learn historical information about the virus. This technology can detect telemetry, complex maintenance robotics and monitoring intelligence. These can be developed to integrate multiple virus-related information. All of these will be coordinated by health professionals. Frequently testing should be done to ensure continued readiness to protect against emergency disasters.

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