Drivers Emotion Recognition using Deep Learning model with Cognitive Intelligence - Prashant Baste (International Journal of Intelligent Systems and Applications in Engineering, 2024)
Research & Development of Intelligent/Smart systems is in progress now-a-days. One of the most interesting areas among this is smart cockpits. Smart Cockpit can identify emotions & help drivers to be more productive. This ecosystem includes self-learning of correct emotion recognition, interpretation & decision making. This Research will cover behavioral analysis/psychology, machine learning, artificial intelligence, signal processing, computer vision and human & computer interaction. Emotions are directly linked with productivity, performance & efficiency of any human. People with happy emotions can focus on activity which leads to more efficient results. Emotion recognition is one of complex & difficult to identify, hence many researches are going on in the same field. Majority of research is based on a single input that is facial expressions and images. Since Facial muscles around the nose & eyes contribute a lot in emotions expressions, it is most used. Using a single mode of input signals (facial expressions recognition) has challenges of manipulation of expressions & thus results are not so accurate. Along with facial expressions additional input signals such as EEG, ECG, Skin Conductivity, respiration, eye movement signal helps to measure emotions more accurately & on that basis further actions can be taken. A smart cockpit having capability of Human-Machine interaction (identifies correct emotions & take needful action) will help to improvise safety, comfort, and driver’s acceptance. Emotions such as Anger, Sadness, Fear, and Disgust are having a negative impact on safety driving where Happiness & Neutral emotions help in improving driving safety and Surprise shows alertness of individuals while driving. Music plays a vital role in controlling emotions, controlling, or converting negative impacting emotions to positive impacting emotions. Thus, this module can be used for increasing safety & comfort of driving. Multiple Machine Learning algorithms such as Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), Long Short-Term Memory Networks (LSTM), Deep Canonical Correlation Analysis (DCCA), Bimodal Deep Auto Encoder (BDAE) helps in identify Emotions.