Abstract: This disclosure relates generally to a system and method to identify a plurality of noises or their combination to suppress them and enhancing the deteriorated input signal in a dynamic manner. It identifies noises in the audio signal and categorizing them based on the trained database of noises. A combination of deep neural network (DNN) and artificial Intelligence (AI) helps the system for self-learning to understand and capture noises in the environment and retain the model to reduce noises from the next attempt. The system suppresses unwanted noise coming from the external environment with the help of AI based algorithms, by understanding, differentiating, and enhancing human voice in a live environment. The system will help in the reduction of unwanted noises and enhance the experience of business and public meetings, video conferences, musical events, speech broadcasts etc. that could cause distractions, disturbances and create barriers in the conversation.

Abstract: State of art techniques utilize active systems for stronger suction in surface crawlers while the passive approaches have limitation in providing consistent grip while moving across curved surfaces or dents. Embodiments herein provide an autonomous surface crawling robot for crawling over surfaces using electro-mechanical assembly for creating strong suction force and enabling the robot to smoothly crawl over flat surfaces, horizontal/vertical/inclined surfaces, curved surfaces, and surfaces with dents. Battery powered motors are used for only mobilization, while mechanical assembly generates suction to provide consistent grip across different type of surfaces. A dual flexible cam profile assembly including a cam profile and a guide rail generates required suction and addresses the technical challenge of maintaining suction across varying surfaces without using external power for suction generation.

Abstract: This disclosure relates generally to a system and method to identify a plurality of noises or their combination to suppress them and enhancing the deteriorated input signal in a dynamic manner. It identifies noises in the audio signal and categorizing them based on the trained database of noises. A combination of deep neural network (DNN) and artificial Intelligence (AI) helps the system for self-learning to understand and capture noises in the environment and retain the model to reduce noises from the next attempt. The system suppresses unwanted noise coming from the external environment with the help of AI based algorithms, by understanding, differentiating, and enhancing human voice in a live environment. The system will help in the reduction of unwanted noises and enhance the experience of business and public meetings, video conferences, musical events, speech broadcasts etc. that could cause distractions, disturbances and create barriers in the conversation.