A method to crowd source pothole marking on (Indian) roads

In, India, roads and potholes are 2 sides of the same coin! You cannot think of one in exclusion of another. This post of mine looks at a novel technique of rapidly identifying & marking potholes in (Indian) roads. This approach can be used for any city in the world but is very pertinent to Indian roads.

This idea of mine provides a technique of quickly marking pothole in roads through the method of crowd sourcing

 

Introduction: It is a well known fact that Indian roads are riddled with potholes. Some may even say that there are potholes with patches of road in between them. This disclosure looks at a novel technique of rapidly identifying & marking potholes in (Indian) roads. The approach can be used for any city in the world. However this disclosure will focus on Indian roads. This disclosure proposes a novel technique of crowd-sourcing the marking of potholes on roads rather than having any single government body (NHAI etc) travel on roads to make the markings.

Description: This post proposes a novel crowd-sourced method for pothole marking that will be easy to conduct and extremely rapid The crowd-sourced pothole marking application will be made of the following components namely Pot-hole marking app, Backend server, Map Matching utility, Pothole ranking utility.

Pothole marking App: A location based smartphone app will need to be created preferably both on Android and iOS. The app will display the map with buttons to mark the following

a)   Points in map of potholes

b)   Bad segments of roads with potholes

Backend Server: The backend server will collect all the data (marked potholes) and bad segments of roads and will update a database.  A map-matching utility will map the latitude, longitude of the marked point on to a map. When the geographical location of a pothole is received (latitude, longitude) the backend server will also store the time stamp.

Pothole ranker: This module will run on a periodical basis, say once every 3 minutes. This module will determine all the potholes that have been entered in the last 3 minutes and add to the accumulated count of marked potholes. Each marked pothole will hold the count of the marks and also the time stamp of the mark. It will also rank the criticality of the pothole based on the accumulated count of potholes over the period.

The pothole ranker will maintain the following metrics

  1. Pothole criticality = Total accumulated count/ Total time
  2. Pothole impact measure = Max rate of pothole marks (Pothole marks/hr)
  3. Bad stretches of roads with many potholes =

Number of adjacent potholes/ Distance in meters

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Description: This how the scheme will work in practice. The app will be uploaded into Google Play and Apple’s App store.  All users who would like to participate in the pothole marking exercise can download and install the app on their smart phones. These users when they are traveling on a road can mark potholes as they encounter them. It is assumed that the users are passengers in vehicles or pillion riders. The fact that users all over the city can simultaneously mark potholes as they encounter them will make the gathering of pothole data rapid and extremely accurate. A map of a city would need to be generated with the circles/points for locations of potholes, color-coded appropriately. We could use the color red for higher ranked potholes and yellow for lower ranked potholes with intermediate colors like purple, pink etc.  This data can then be used by Government bodies in addressing roads in fixing the roads.

There are three advantages of crowd sourcing the pothole marking

1)   The process of gathering data is rapid

2)   Roads where the traffic is heaviest will have potholes with a higher rank and can be addressed first

3)   The process will be very accurate

Crowd sourcing of pothole marking will have the following benefits

  1. The marking of potholes will be extremely rapid
  2. The potholes will be ranked based on accumulated count
  3. Ranking of potholes can be done on

– Total accumulated count/Total time

– Rate of pothole mark

– Critical segments with major potholes

4. It will be easy to segregate

– Critical potholes
– Max impactful potholes
– Bad road segment

  1. The process will be very accurate

Conclusion: The process of crowd sourcing pothole marking of Indian roads will be extremely efficient in marking potholes and bringing it to the attention of the Government.

A map of a city with the circles for locations of potholes, color-coded appropriately, to indicate higher marked potholes versus the lower ranked potholes could be generated. This map can be used to bring to the attention of the government the really bad roads and terrible road segments. Rather than having a couple of vehicles trying to ply roads and mark roads this will be very fast and extremely accurate.

Afterword: The concept of crowd sourcing for traffic is not new. Waze, which Google bought for close to $2bn does just that. It crowd sources traffic conditions and alerts users of the app. Also I did a Google search on using mobile apps for potholes marking and, not surprisingly, there were others who had also thought of a similar idea in Boston & Florida see the links below

  1. http://www.cityofboston.gov/doit/apps/citizensconnect.asp
  2. http://dailycrowdsource.com/20-resources/projects/421-crowdsourced-pothole-database-to-track-road-repair

However, I personally think that the situation in India is different, where there are ‘roads in between potholes’ ;-). While in the above 2 cases in US, only the location of the potholes is important, my idea ranks potholes based on the accumulated count and the rate of pothole marks. These metrics can be used by the government in addressing those sections of roads where the potholes have a higher rank i.e. where the traffic is highest.

Your thoughts are welcome.

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