Intelligent Monitoring System For Road Environment

Project Title

Intelligent Monitoring System For Road Environment

Project Area of Specialization Internet of ThingsProject Summary

SUMMARY:

The aim of this project is to develop a framework which can create a map of potholes in Hyderabad using information from sensors built into modern smartphones. We shall benchmark the performance of our proposed framework with sensing platform built using gyroscope/accelerometer sensors and an Arduino board. In most of the highly populated cities, there are lots of environmental issues regarding roads such as air pollution ,congestion and most importantly the potholes which are responsible for the accidents. To provide perfect safety to the people, an IOT based prototype will be installed in the car, which will facilitate the user to monitor road environment and choose the best and safe path towards his/her destination .Our project is the designation of framework using Arduino which one can monitor road environment using IMU and some other sensors by embedded systems, which are as follows IMU sensors (MPU9250) contain:

                              

GYROSCOPE: A gyroscope measures either changes in orientation (regular gyro or integrating rate gyro) or changes in rotational velocity (rate gyro).
ACCELEROMETER: An accelerometer measures accelerations. This is useful to measure changes in velocity (directly, as the acceleration is the first time derivative of the velocity).
MAGNETOMETER:A magnetometer measures magnetic fields. Because the earth has a significant magnetic field, the magnetometer can be used as a compass.

Other than IMU sensors ,we have used also some other sensors such as:

MQ135: This sensor is used to measure different types of gases in air i.e. Carbon monoxide, Carbon dioxide etc. In other words it measures the air quality in ppm(Parts Per Million).                  

                                 

HCSR04:This sensor is simply used to measure the distance from the object which is in front of&

Project Objectives

Objectives of this project are as follows:

•    To develop a module which can be used to acquire inertial movement data which can then be used to identify potholes on roads using machine learning.
•     To investigate the hypothesis that air pollution and traffic congestion increases in location where there are potholes, as compared to locations where there are no potholes.
•     To create a user-friendly map of potholes which can be easily interpreted by city planning authorities.
   

Project Implementation Method

We have summarized the Project Implementation Method as follows, technical details of the project as provided in Technical Details of Final Deliverable section:

• The first step is to undertake a survey of research literature which focusses on pothole detection using accelerometer data. We will also have meeting with faculty from the City & Regional Planning department of Mehran University in order to receive their requirements. This step has provided an informed foundation for the project.
• The second step is to understand the configuration, calibration, and working of MPU-9250 motion tracking device, which we are using to acquire movement data. 
• The third step is to develop a motion tracking module which can be used to capture the movement of an automobile and store in an SD card. This is the most critical part of the project and we shall endeavor to build a high-quality module.
• The fourth step is to setup automobile movement data-acquisition from smartphones, which also have inertial movement sensors built into them. We will benchmark the quality of data acquired from the MPU-9250 against the data acquired from smartphones.
• The fifth step is to integrate air quality and proximity sensors with our module. These sensors will be used to test the hypothesis that the existence of potholes leads to increase in air pollution as well as congestion because many automobiles are stuck in a particular part of the city.
• The sixth step is to design data acquisition plan for Hyderabad City. Here, we will plan and map locations using GPS and the Google Maps service.
• The seventh step is based on machine learning and can be started once we have sufficient data. Here, we will train classifiers based on Logistic Regression and Support Vector Machines algorithms in order to identify changes in automobile when they traverse potholes.
• The final step is to present our work to relevant city planning authorities of Hyderabad City.
   

Benefits of the Project

The expected benefits of our project are summarized as follows:

•     Our project addresses the serious issue of transportation which causes damages worth thousands of rupees on each one of us. We propose intelligent road monitoring system can identify potholes using inertial sensors and machine learning based processing of data.
•     As part of the project, we are also conducting a data science inspired research where we want to investigate whether potholes leads to increase air pollution due to automobile engine fumes and also traffic congestion. This information can be very useful for city planning authorities.
•     Finally, we are building a Pakistan developed solution rather than a foreign import, which can help our country save vital foreign exchange. We plan to continue working on this module and develop towards a startup.

Technical Details of Final Deliverable

In most of the highly populated cities, there are lots of environmental issues regarding roads such as air pollution ,congestion and most importantly the potholes which are responsible for the accidents. To provide perfect safety to the people, an IOT based prototype will be installed in the car, which will facilitate the user to monitor road environment and choose the best and safe path towards his/her destination .Our project is the designation of framework using Arduino which one can monitor road environment using IMU and some other sensors by embedded systems, which are as follows .IMU sensors (MPU9250) contain:
GYROSCOPE: A gyroscope measures either changes in orientation (regular gyro or integrating rate gyro) or changes in rotational velocity (rate gyro).
ACCELEROMETER: An accelerometer measures accelerations. This is useful to measure changes in velocity (directly, as the acceleration is the first time derivative of the velocity) and changes in position (by integrating the signal). They are usually used for measuring small movements. Also note that gravity acts like a continuous acceleration upward (via Einstein's equivalency principle), so a multiple-axis accelerometer can also be used as an absolute orientation sensor in the UP-DOWN plane.
MAGNETOMETER:A magnetometer measures magnetic fields. Because the earth has a significant magnetic field, the magnetometer can be used as a compass.
Some other sensors are as follows:
MQ135: This sensor is used to measure different types of gases in air i.e. Carbon monoxide, Carbon dioxide etc. In other words it measures the air quality in ppm(Parts Per Million).                                           
HCSR04:This sensor is simply used to measure the distance from the object which is in front of it. This sensor is used to measure the congestion.
SD CARD MODULE:SD Card Module is an SPI interface based module. It is used for transferring data to and from a standard SD card. 

To acquire data,we will install an IMU(MPU9250) sensor in or near shock absorber, so that we can take values of Gyroscope, Accelerometer and Magnetometer, there readings will vary with the variation of shock absorber and the car itself. And then we'll install the other sensors such that proximity/HCSR04 and MQ135 in front of the car to measure the congestion and air quality of the environment. That's how we'll take out data via our hardware. Which then will be compared with the data which will be taken out from the applications installed in the smartphones. All the data will store in SD card module and on cloud(online). Data will also be stored from the GPS in order to map potholes to Google maps. Lastly, after the data collection most importantly we'll apply machine learning(subset of Artificial  Intelligence) in our project using some of the algorithms which will make the model understand the road environment by itself. Our hardware will be powered using the Lithium Ion(rechargeable) batteries.

We have designed our prototype as shown below:

Final Deliverable of the Project HW/SW integrated systemCore Industry TransportationOther Industries IT Core Technology Artificial Intelligence(AI)Other Technologies Internet of Things (IoT)Sustainable Development Goals Sustainable Cities and CommunitiesRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	40600
Arduino Nano	Equipment	5	500	2500
MPU-9250 sensor	Equipment	10	1000	10000
Rechargeable Batteries	Equipment	10	400	4000
PCB Board	Equipment	5	100	500
Acrylic Model	Miscellaneous	5	1100	5500
Soldering 50mg wire	Equipment	12	100	1200
Jumper Wires	Equipment	24	100	2400
Soldering Machine	Miscellaneous	3	1000	3000
MQ135 sensor	Equipment	10	550	5500
HCSR04 sensor	Equipment	10	200	2000
16 x 2 Character LCD Module	Equipment	10	400	4000