ML-DP: A Smart Emotion Detection System for Disabled Person to Develop a Smart City

A disability is one of the main issues that has presented and continues to present difficulties. Disability has been and continues to be a source of frustration since it is viewed as a constraint, a mental, physical, and cognitive handicap that restricts the individual's involvement and growth. As a result, great effort is put into eliminating this kind of restriction. The difficulty that people with disabilities encounter are addressed by this initiative. People with disabilities must rely on others to meet their needs. Machine learning is doing a fantastic job to construct a smart city and offering a secure existence for handicapped people. Because developing a smart city is feasible if we can intelligently treat our handicapped people. To inform the caretaker of the needs, this project develops an emotion recognition system based on landmarks. This study uses a convolutional neural network to recognize facial emotions to comprehend the feelings of impaired people. Only wireless button-based communication, according to the present method, can alert the caregiver that a handicapped person needs anything. This has the drawback that the handicapped person must be cognizant to provide the command. Additionally, as of right now, Assistive Technology has not been incorporated to offer automated assistance to impaired people based on their mood. This research makes use of 468 facial landmark extraction, machine learning, and emotion categorization. Based on the separation of several facial cues, this method can identify seven different types of emotions. The many emotions include anger, fear, sadness, disgust, surprise, joy, and neutrality. The technology will alert the caregiver when the emotion is identified as fear or anger. Additionally, if the emotion is detected as sad, an upbeat song will play until the mood changes. Finally, the caretaker receives emotional value from the system. Thus, our suggested solution takes care of the issue if the caregiver is not close by.