CYBER SENTINEL: SECURE LOGIN WITH VULNERABILITY SCAN

Abstract

Owing to the emerging technologies, innovations are introduced in the context of car maintenance and environmental preservation. These novel systems provide increased access to vehicle diagnostics, and support precise and instantaneous measurement of engine efficiency as well as carbon emissions. Environmental well-being and atmospheric purity are concerns of considerable seriousness that should be addressed with the highest precautions and preventive protocols. Excess carbon emission by engines has been a huge issue in recent years, calling for predictive emission monitoring and pre-emptive engine maintenance. For the development of consumer confidence and eco-friendly transport, there is greater need for focus on the issue of emission prediction and engine cleaning. Carbon deposit inside engines, if undetected, results in excess fuel consumption and emissions. For its solution, a better method using a Modified Convolutional Neural Network (CNN) algorithm is presented. Through the application of the new approach, carbon emission patterns can be correctly predicted and engine cleaning can be scheduled accordingly, in turn providing improved engine performance and reduced environment degradation.