Review 3 Report

ASSESMENT REPORT ON Team ID & Title: 11

Mining and suggestion using the data obtained through pothole detection Submitted

as part of CSE3999-Technical

Answers for Real World Problems

Reg. No: 16BCE0042 Name: Nannapaneni Thejesh Reg. No: 15BCE0242 Name: Karthik

To

Sasikala R School of Computer Science and Engineering

April 2019

Index Chapter Topic

Page No.

1

Abstract & Keywords

1

2

Objectives

2

3

Literature Review

3.1.

National Status

3

3.2.

International Status

4

4

Requirements

5

4.1.

Hardware

6

4.2.

Software

7

5

Design

8

6

Invention Details

6.1.

Objects of the Invention

9

6.2.

Summary of Invention

9

6.3.

Brief Description of the Drawings

9

6.4.

Detailed Description of the Invention

9

6.5.

Working Examples

10

6.5.1.

Working Example 1

10

6.5.2.

Working Example 2

10

6.5.3.

Working Example 3

10

7

Implementation

7.1.

Pseudo Code

11

8

Results

12

9

Conclusions

13

10

References

14

Chapter 1 ABSTRACT Roads have been flooded with the traffic. It has become difficult to manage this traffic. This is the prime need behind making a vehicle intelligent enough to aid driver in various aspects. One of the existing methods is that capturing the pot holes with camera and subjecting it to some techniques in image processing to detect pot holes. It is time seeking and not that accurate enough to detect the exact existence and width of the potholes. So here we are with additional features like if the driver goes in the same way again, our system intimates him/her beforehand and its efficiency is high due to use of ultrasonic sensors. One of the issues is regarding connectivity. All the way till the end of use of vehicle, the system should be connected to the local database so that it could load the location and information of potholes. With this idea we can prevent the accidental damages caused to the vehicles and passengers due to these potholes on the roads.

Keywords: Potholes, Ultra-Sonic Sensors, Micro Controller, Vehicle, Road, Driver, Speed Breakers, Connectivity, Detection, Access Point

CHAPTER 2 OBJECTIVES

1

To develop a real-time user-friendly application and ultrasonic sensors for detecting discontinuities along the terrain.

2

Updating information (like location, position) into the database about the discontinuities in the terrain and adding it to the information broadcast.

3

Because of ultrasonic sensors, driver will get notified well in advance about any discontinuities in the terrain and adding it to the information broadcast.

4

We will develop a quick-time application which will help in signalling the driver about a pothole as quickly as possible

5

Hence main objective of our project is to prevent the car and the passengers inside from any damages and inconveniences.

CHAPTER 3 LITERATURE REVIEW

3.1.

National Status:

1. Shonil Vijay (2006), IIT Bombay: The objective of this project is to develop a low cost vision-based driver assistance system over FPGA, to provide a solution of detection and avoidance of potholes in the path of a vehicle on road. This project used an FPGA model to deploy image processing algorithms efficiently so that the output can be achieved in real time. 2. Sachin Bharadwaj and Golla Varaprasad (2013), IET Digital Library: This study discusses a solution for detection of potholes in the path of an autonomous vehicle operating in an unstructured environment. Here, a vision approach is used since the simulated potholes are significantly different from the background surface. Furthermore, using this approach, pothole can only be detected in case of uniform lighting conditions. The solution to the problem is developed in a systematic manner. Initially, a specific camera and frame grabber are chosen, then camera is mounted on top of the autonomous vehicle and the images will be acquired. Then, a software solution is designed using MATLAB.

3. Gunjan Chugh , Divya Bansal and Sanjeev Sofat(2014), PEC University, Chandigarh: This paper presents a detailed survey of methods for detecting road conditions. Form the survey, it is noted that the most commonly used sensors accelerometer and GPS. 4. Shambhu Hegde and Harish (2014), International conference, Hyderabad: This paper aims at proposing a novel pothole detection system, which assists the driver to avoid potholes on the roads by giving prior warnings. The idea is to build a robot vehicle that is capable of detecting the potholes and transferring this information to the nearby vehicles in the vicinity.

5. Aniket Kulkarni and Nitish Mhalgi (2014), V.E.S. Institute of Technology, Mumbai: This paper investigates an application of mobile sensing detection of potholes on roads. They described a system and an associated algorithm to monitor the pothole conditions on the road. This system, that they call the Pothole Detection System, uses Accelerometer Sensor of Android smartphone for detection of potholes and GPS for plotting the location of potholes on Google Maps using machine learning concepts.

3.2. International Status: 1. Larry Matthies and Alonzo Kelly (1996), Jet Propulsion Laboratory, USA: This paper describes how to detect obstacles during off-road autonomous navigation, unmanned ground vehicles (UGV's) must sense terrain geometry and composition (i.e. terrain type) under day, night, and low-visibility conditions. To sense terrain geometry, we have developed a real-time stereo vision system that uses a Datacube MV200 and a 68040 CPU board to produce 256 x 45-pixel range images in about 0.6 seconds/frame. 2. Reinholds Zviedris (2011), University of Latvia, Lativa: This paper describes lessons learned from their field tests, which have exposed the deficiencies in terms of collected data quality. They are developing a vehicular participatory sensing application using Android smart-phones for pothole detection. Nevertheless, the tests provide invaluable experience for planing future field tests and improvements to the test execution procedure for vehicular sensing researchers.

3. Christain Koch and Ioannis Brilakis (2011), Elsivier: In this paper they present a method for automated pothole detection in asphalt pavement images. In the proposed method an image is first segmented into defect and non-defect regions using histogram shape-based thresholding. Based on the geometric properties of a defect region the potential pothole shape is approximated utilizing morphological thinning and elliptic regression. 4. He Youquan and Wang Jian (2011), International Congress, Shanghai: In order to detect the three-dimensional cross-section of pavement pothole more effectively, this paper proposes a method which employs optical imaging principle of three-dimensional projection transformation to obtain pictorial information of pothole's cross-section in pothole detection. Multiple digital image processing technologies, including: image pre-processing, binarization, thinning, three-dimensional reconstruction, error analysis and compensation are conducted in the series of image analysis and processing. Experimental results indicate that the method is markedly superior to traditional methods in many aspects.

5. X. Yu and E.Salari(2011), IEEE Interational Conference, Mankato,USA: In this paper, they introduced an efficient and more economical approach for pavement distress inspection by using laser imaging. After the pavement images are captured, regions corresponding to potholes are represented by a matrix of square tiles and the estimated shape of the pothole is determined. The vertical, horizontal distress measures, the total number of distress tiles and the depth index information are calculated providing input to a three-layer feed-forward neural network for pothole severity and crack type classification. The proposed analysis algorithm is capable of enhancing the pavement image, extracting the pothole from background and analysing its severity.

CHAPTER 4 REQUIREMENTS 4.1. Hardware Requirements 4.1.1. List of Hardware Components (Example) a) Arduino Uno

b) GPS module

c) Ultrasonic Sensor

d) USB 2.0 Cable

e) Breadboard

f) Resistors-10k, 270k and 330k ohm

g) Jumper wires

4.1.2. a. Description of Hardware Component:

Fig. 1: Raspberry pi Name of Item: Arduino Uno – Model: Atmega328P – Vendor: Generic – Price: ₹ 455 – Spec: Operating voltage 5V, Input Voltage 7-12 V, Digital I/O pins-14, Analog input pins-6.

Component Functionality: Small size, cheap and open hardware, which runs many of the main components of the board– CPU, graphics, memory, the USB controller, etc.

Application: 1) Arduino Based Home Automation System 2) Arduino Based Auto intensity control of Street lights Reference URL: https://www.amazon.in/Uno-ATmega328P-Compatible-ATMEGA16U2Arduino/dp/B015C7SC5U/ref=sr_1_4?keywords=arduino+uno&qid=1554391438&s=compu ters&sr=1-4

Name of Item: Ultrasonic sensor – Model: HC-SR04 – Vendor: Balaji electronics, Vellore – Price: ₹ 150 – Spec: 5V, 15 mA, 40 Hz, range = 2 - 400 cm

Component Functionality: Measure distance to an object by using sound waves. Application: 1) To measure Tank Level. 2) Distance Measurement. 3) Robotic sensing. 4) Vehicle detection for car wash and automotive assembly, etc.

Reference URL: https://www.electroschematics.com/8902/hc-sr04-datasheet/

Summary of Components in Tabular form: S.No

Item

Model

Spec

Vendor

Price In Rs.

1

2

Arduino Uno

Ultrasonic sensor

Operating voltage 5V, Atmega328P Input Voltage 712 V, Digital I/O pins-14, Analog input pins-6.

Generic,

HC-SR04

Balaji

5V, 15 mA,

455

Amazon

150

40 Hz, range electronics, = 2 - 400 cm 3

GPS module

Neo6Mv2

Vellore

With Antena Xcluma,Amazon

1000

and built in EEPROM 4

Breadboard

GL-12

-

Balaji ele.

60

5

Resistors

10k, 270k,

-

Balaji ele.

2

330k 6

Jumper wires

Female-male Balaji ele.

12

Connection

Total 1324/Table 1: Summary of Hardware Components 4.2. Software Requirements S.No

Item

versions

Vendor

Price

Description

Reference

1

Arduino

March

online

Free

Debian based

microsoft store

IDE

2019

computer OS for Arduino Uno

2

Python IDLE

3.7.0

online

Free

A powerful python editor

Table 2: Summary of Software Components

www.python.org

CHAPTER 5 Design

Arduino is connected to Ultrasonic sensor and GPS module. Data is stored into cloud where a excel file containing Street name, number of potholes and latitude, longitude (as if now) values will be given. This excel sheet is then used by data mining algorithms to get helpful predictions.

CHAPTER 6 INVENTION DETAILS 6.1.

Objects of the Invention: It is common knowledge that roads are fraught with many dangers such as bumps, manholes, large stones, etc. without adequate warning signs, making travel, both on foot as well as on an automobile very risky, especially at night. There is a need for a reliable and robust early warning system which would accurately detect abrupt discontinuities in terrain like potholes, manholes, bumps, etc. which can be used by pedestrians.

6.2.

Summary of Invention: One of the main difficulties in developing countries is maintenance of roads. Well maintained roads contribute a major portion to the country’s economy. Identification of pavement distress such as potholes and humps not only help drivers to avoid accidents or vehicle damages, but also helps authorities to Maintain roads. Hence its is an important issue to find out the hurdles on the road that are dangerous to the vehicle and the driver inside the vehicle even.

6.3

Brief Description of the Drawings: In the circuit made, a 330-ohm resistor is connected to the ultrasonic sensor. Another 470-ohm resistor is connected to the two pins of the raspberry pi with male to male connection wires.

6.4.

Detailed Description of the Invention:

6.5.

Working Examples

6.5.1

Working Example 1: Production Line Sensors: Ultrasonic sensors can be applied to the manufacturing process for automated process control on the factory floor while also being an indispensable tool for companies to maximize efficiency through precise measurement and control.

Ultrasonic sensors can streamline the production processes.

6.5.2

Working Example 2: Distance Measurement: Ultrasonic sensors can measure the distance to a wide range of objects regardless of shape, color or surface texture. They are also able to measure an approaching or receding object.

6.5.3

Working Example 3: Tank Level: Liquid level sensors are integral to process control and inventory management in many industries. At Migatron, we engineer two types of level sensors, point level sensors (proximity sensors which is a type of ultrasonic sensor) and continuous level sensors (analog sensors). The type of sensor appropriate for your liquid level measurement depends on the application.

CHAPTER 7 IMPLEMENTATION 6.1. Pseudo Code

CHAPTER 8 RESULTS 6.1. Snap shots

CHAPTER 9 Conclusions Taking into account the current road scenarios, there is a need to devise a system which warns the driver about the upcoming potholes. Many on-going projects in the field of vehicular networks are working in the direction of providing driver with relevant information about roads and traffic movements. We present here, a novel idea of Pothole Detection & Warning System which aims at providing appropriate information to the driver about potholes. We have implemented this system which would continuously detect the potholes on the road and detect the hardware’s location and send the data to the server side. In this document, we have described the working, the hardware requirements, the software requirements that it will use to run the system. The data obtained from here is being can be given to the concerned road management authority for the further procedures. Therefore, driver’s safety may be improved with the establishment of real-time pothole detection system for sharing the pothole information. If such system is implemented it could result in various helps to the public as well as the governmental body for the development of the country. In this project, various choices for implementing the System have been studied and compared to each other on various criterion. We intend to develop a system which characterize road condition into categories like smooth, moderately uneven and highly uneven from the results of the experiments through our project.

Chapter 10 REFERENCES

1.

R Gass, J Scott, C Diot, “Measurements of In-Motion 802.11 Networking”, IEEE Workshop on Mobile Computing System and Applications, 2006 .

2.

X Zhang, JK Kurose, BN Levine, D Towsley, H Zhang , “Study of a bus-based disruption-tolerant network: mobility modeling and impact on routing”, 13th annual ACM international conference, 2007.

3.

“http://www.its.dot.gov/vii”, RITA | ITS | Vehicle Infrastructure Integration, JAN 2007.

4.

“http://dev.emcelettronica.com/datasheet/st/LIS3L06AL”, Datasheet of ST LIS3L06AL accelerometer, JAN 2008.

5.

“http://www.gps.gov/”, Global Positioning System, JAN 2007.