drivers safety by emotion sensing using mmwave radar7042
For advanced driver safety systems, monitoring a driver's emotional state is the most suitable option for predicting the driver?s capacity to supervise or operate the vehicle in cases of unexpected road events and to facilitate better in-car service. Heart rate is a key indicator for assessi
2025-06-28 16:32:12 - Adil Khan
For advanced driver safety systems, monitoring a driver's emotional state is the most suitable option for predicting the driver’s capacity to supervise or operate the vehicle in cases of unexpected road events and to facilitate better in-car service. Heart rate is a key indicator for assessing health, stress and fitness. The main target of our force project is to develop an idea of an AI-based safety system that will help in reducing the number of road accidents and fatalities by analyzing driver's emotions i-e fatigue, stress, tiredness (drowsy) or sadness using mmwave radar that will be monitoring the heart rate, breathing rate, which will be useful in identifying the cause of drivers emotion there will be a mobile application that will be providing us the solution or suggesting us suitable precautions that could help in enlightening the mood and emotion of the driver.
Project ObjectivesIn the majority of the models, the primary objective is based on safe driving behavior. As emotion is an instantaneous function hence we would provide a contactless emotion sensor, as it is not practically possible for a driver to carry a sensor that needs contact all the time, which would detect the stress, fatigue or tiredness level of the driver to avoid the risk of accidents.
Moreover, our other goal is to make an android application that continuously observes driver’s vital signs to assist in decision making that provides guidance to the driver in a loud and clear manner. We will be connecting DS18B20 temperature sensor and gps to our raspberry pi for predicting the drivers on-spot emotion that is fatigue, drowsiness and stress.
Project Implementation Method
This work classified three main causes of driving accidents, viz. distraction, fatigue, and aggressive driving behavior. Our project specifically focuses on the safety of drivers, the driver’s attentiveness is the primary element for safe driving. Distraction and fatigue are the main causes of road accidents. The studies reveal that several biological and physiological measurements can accurately detect a driver’s mental engagement and for this purpose we have used the mm wave radar for the emotion sensing of the driver by observing their ECG which would provide an innovative way of minimizing the risk of accidents due to fatigue or tiredness . This project would add a very attractive feature to the automobiles for the people who are involved in long distance travelling frequently.
Technical Details of Final DeliverableOur project is a hardware and software based project which is developed for emotion sensing by using mmwave radar, a method we used for the evaluation of emotions is machine learning technique based on humans ECG. We will be making an AI Model that predicts the driver's health condition throughout his journey and pairing algorithms that matches the predicted health condition to the solution that will be provided using our mobile application
Final Deliverable of the Project HW/SW integrated systemCore Industry HealthOther IndustriesCore Technology Artificial Intelligence(AI)Other TechnologiesSustainable Development Goals Good Health and Well-Being for People, Industry, Innovation and InfrastructureRequired Resources| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Total in (Rs) | 64484 | |||
| Raspberry pi 3 model-b | Equipment | 1 | 6800 | 6800 |
| DS18B20 temperature sensor | Equipment | 2 | 200 | 400 |
| GPS NEO | Equipment | 1 | 1450 | 1450 |
| IWR1642 mmWave radar sensor | Equipment | 1 | 47834 | 47834 |
| Miscellaneous | Miscellaneous | 1 | 8000 | 8000 |