Abstract:
Traffic accident is one of the contributing factors of the death that happened around the world. From various types of drivers that are usually found in the traffic, moto...Show MoreMetadata
Abstract:
Traffic accident is one of the contributing factors of the death that happened around the world. From various types of drivers that are usually found in the traffic, motorcycle drivers have a relatively higher risk compared with other types of drivers. Therefore, there is a need for a system that is capable to detect dangerous behavior from the driver and gives an alert when abnormal behavior is detected. To develop it, we choose the 2 basic sensors to detect the movement from a driver, which are Accelerometer and Gyroscope. These sensors have been integrated into a smartphone. For the classification process, we proposed an Enhanced Multi-Layer Perceptron (MLP). The complexity of the model is reduced to ensure that our proposed system will be able to work in real-time conditions and in a limited-resources environment. In our model, we use the combination of ReLU and Softmax function, two of the famous Activation function, to enhance the performance of our model. The level of accuracy of our model achieved 97.5% with an average computational time of 45 ms. This proved that our model works better than the previous research with the same dataset.
Published in: 2021 International Electronics Symposium (IES)
Date of Conference: 29-30 September 2021
Date Added to IEEE Xplore: 08 November 2021
ISBN Information:
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- IEEE Keywords
- Index Terms
- Abnormal Behavior ,
- Multilayer Perceptron ,
- Activation Function ,
- Complex Models ,
- Computation Time ,
- Traffic Accidents ,
- Softmax Function ,
- Gyroscope ,
- Real-time Conditions ,
- Rectified Linear Unit Function ,
- Types Of Drivers ,
- Neural Network ,
- Model Performance ,
- Accuracy Of Model ,
- Convolutional Neural Network ,
- Artificial Neural Network ,
- Machine Learning Models ,
- Output Layer ,
- Multilayer Perceptron Model ,
- Artificial Neural Network Model ,
- Hidden Layer ,
- Network In Order ,
- Accelerometer Sensor ,
- Input Layer ,
- Driver Behavior ,
- Recurrent Neural Network ,
- Low Computational Time ,
- IIR Filter
- Author Keywords
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Abnormal Behavior ,
- Multilayer Perceptron ,
- Activation Function ,
- Complex Models ,
- Computation Time ,
- Traffic Accidents ,
- Softmax Function ,
- Gyroscope ,
- Real-time Conditions ,
- Rectified Linear Unit Function ,
- Types Of Drivers ,
- Neural Network ,
- Model Performance ,
- Accuracy Of Model ,
- Convolutional Neural Network ,
- Artificial Neural Network ,
- Machine Learning Models ,
- Output Layer ,
- Multilayer Perceptron Model ,
- Artificial Neural Network Model ,
- Hidden Layer ,
- Network In Order ,
- Accelerometer Sensor ,
- Input Layer ,
- Driver Behavior ,
- Recurrent Neural Network ,
- Low Computational Time ,
- IIR Filter
- Author Keywords