Train Comfort analysis using acceleration measurements and neural network

The railway is the backbone of a country?s economy as passengers rely heavily on it due to its affordability. However, in Pakistan, not only the safety of the railway is compromised but also its ride comfort. There is an absence of any standardization platform status that could rate the riding stand

Project Title

Train Comfort analysis using acceleration measurements and neural network

Project Area of Specialization

NeuroTech

Project Summary

The railway is the backbone of a country’s economy as passengers rely heavily on it due to its affordability. However, in Pakistan, not only the safety of the railway is compromised but also its ride comfort. There is an absence of any standardization platform status that could rate the riding standards of the trains currently operational in Pakistan. To address this, we are aimed at providing a solution that will not only analyse the railway ride comfort based on acceleration measurements but also will acquire brain signals, which will exhibit the current comfort of the passengers. This proposed instrumentation will comprise an EEG headset (that will analyse the somatosensory cortex of the Parietal lobe of the brain) and a train mounted accelerometer module (in order to understand the effect of train vibration on the human comfort level), which will be tested on volunteers from different age groups on almost all of the operational trains of Pakistan. The data collected will pass through a machine learning-based data analytic model which will provide the comfort rating of the various trains. This study will ultimately help passengers from different age groups in making the decision of which train they should choose for travelling. Moreover, as this project is in collaboration with the Pakistan Railways, they can use this study in determining their fair rates.

Project Objectives

The project objectives of this research work are aligned with SDG: Good Health and Well-being and ultimately focus on serving the citizens of Pakistan. The objectives are mentioned as follows:

1. Development of a hardware and software model using Jetson Nano with Electroencephalogram (EEG) and accelerometer sensors.
   • To collect data and analyse it for the passengers’ train comfort using an acceleration measurement and EEG instrumentation based on the data acquired from various age group volunteers.
2. To develop a hardware and software model for data collection, which will be conducted by Jetson Nano’s integration with the EEG and accelerometer sensors.
   • To collect the electrical signal from the brain, we will use an EEG sensor on the somatosensory cortex of the Parietal lobe which is responsible for receiving and processing sensory information. To collect the data on train vibration we will use an accelerometer on the seat.
   • To collect the data on the train vibration accelerometer will be mounted on the train.
   • The data aimed to be collected from currently operational trains in Pakistan to develop a database so that, comfort can be analyzed of each train, individually.
   • To conduct comfort analysis of the passenger by correlating the data of accelerometer (train’s vibration analysis) and EEG sensors by using the developed data analytic algorithm with the help of a Neural Network.
   • To analyze the train comfort a developed algorithm by categorizing the level of comfort and discomfort based multi-level data classification algorithm in order to determine the ride comfort.
   • To assign the category of a certain level of comfort, we will check the comfort of pressure points collected from the EEG sensor compared with the vibration on that point received from accelerometers. 
3. To set an online platform that will rate the ride comfort level of all the operational trains.
   • This objective is set to provide an online platform for providing the passengers a platform through which they can decide which train is the most suitable for them to travel. This might introduce a ritual of monthly inspection of the train’s comfort. This will ultimately uplift the current ride standards of Pakistan Railways.

Project Implementation Method

The project implementation method of this project is divided into steps so that it can be easy for us to follow. The steps are mentioned below:

1. Development of the Comfort analyzing Instrumentation: The initial step in this project will be to create instrumentation that will be able to accurately diagnose the train's ride comfort using the processes below:
   • Pressure points identification and validation using EEG sensor: An EEG sensor will be mounted on the Somatosensory cortex of the Parietal lobe of the brain to locate pressure locations. These areas of the brain are frequently mentioned in literature as a factor in determining human comfort. However, we shall validate this region with our planned instrumentation for our satisfaction.
   • Sensory Network Establishment: Following the pressure points validation through our proposed instrumentation, a sensory network will be established using the EEG in form of a specially designed headset module that is flexibly compatible with various head sizes.
2. Data acquisition using accelerometer sensor: Along with the brain signals, an accelerometer module is necessary for this study to gather the data on the train's vibration so that the passengers’ comfort level may be determined by correlating the acceleration measurements with the EEG signals. The accelerometer will be attached to the seats or through-axle box acceleration methodology.
3. Comfort Analysis: This study explores the relationship between acceleration readings and EEG signals and analyses the comfort based on the relationship as well as categorizes the collected data using a data analysis-based neural network method.
4. Model Establishment: In the result, we'll develop instrumentation that can be commercialized and used to set railway travel comfort standards in Pakistan. Pakistan Railways and the National Center of Robotics and Automation – Condition Monitoring Lab, MUET will collaborate on this project.

Benefits of the Project

The project focuses on the main benefits that will revolutionize Pakistan Railways in a better way. The benefits are aligned with the UN’s Sustainable Development Goals.

• SDG 3 - Good Health and Well Being: This project's ultimate purpose is to improve human well-being because, millions of Pakistanis prefer to commute by train, riding on a train with excessive noise and vibration can have a negative impact on mental health, particularly among the elderly. To address this problem, the proposed initiative creates a platform for raising public awareness of the travel comfort of all Pakistani trains currently in service. Passengers are given the option of selecting the most appropriate train for their journey.
• SDG 8 – Decent Work and Economic Growth: This goal will be met by creating a platform of ride comfort standards that will determine the train's comfort based on the comfort ratings provided by our designed instrumentation. A weekly or monthly inspection might help the Pakistan Railways focus on the specific trains that need to be revived in order to improve ride comfort.

Technical Details of Final Deliverable

Developed Solution: This project will provide a solution for ride comfort analysis using a machine learning algorithm developed with the help of a Neural Network which will be used to determine the comfort rating of Pakistan railways.

EEG Headset Instrumentation: This includes the hardware of the project consisting of an EEG sensor integrated into the headset that will be used along with a developed algorithm to analyse the ride comfort along with acceleration measurement to revolutionize the Pakistan Railways ratings.

Final Deliverable of the Project

HW/SW integrated system

Core Industry

Transportation

Other Industries

Medical

Core Technology

NeuroTech

Other Technologies

Artificial Intelligence(AI), Wearables and Implantables

Sustainable Development Goals

Good Health and Well-Being for People, Decent Work and Economic Growth, Industry, Innovation and Infrastructure

Required Resources

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