SIH26056/Smart Automation

Real-time Indian airfare price index

A web platform that scrapes airline portals and travel sites to collect ticket prices, calculates a real-time airfare index, and displays trends on a dashboard for the NSO and RBI.

MoSPI · Data Informatics & Innovation Division (DIID) · Software

Teams already in: Not read yet
Buildable in 36 hours: ModerateOur estimate, from their wording
Hard blockers: NoneNothing you must source first
Submissions close: 15 Sept9 days left

Make this one of our two Compare with others

Signing in saves it for your whole team — everyone on your invite link sees the same two entries. Anything you shortlisted while signed out comes with you.

Submit on sih.gov.in Dataset

Whether this suits your team

What you would have to build

Decomposed from what the description asks for. Nothing added.

01
Web Scraping Engine
An automated Python tool that extracts airfare data from airline websites and travel aggregators while handling anti-bot measures.
02
Data Cleaning Pipeline
A module that processes raw price quotes, removes outliers, handles missing values, and separates base fares from taxes and fees.
03
Index Construction Module
A calculation engine that computes the Airfare Price Index across representative city-pairs and advance-purchase windows.
04
Interactive Dashboard
A web interface that visualises price trends, sector-wise heatmaps, and lead-time elasticity curves.
05
API and Export
An endpoint that allows external users like the NSO and RBI to consume the processed index data.

What they ask for, and what they leave open

Both columns are read off the brief's own wording. Nothing here is inferred from the ministry's name.

They state

The jury will check if your scraping engine successfully bypasses anti-bot measures while respecting ethical limits, how accurately you clean and separate taxes from base fares, and whether your dashboard displays the requested trends and index values.

They never say

exact weights for each city-pair in the index basket
specific database schema to be used

A jury can still ask about these. Decide them deliberately rather than by accident.

What they'll ask you

Generated from the brief's own wording and the competition's published rules — never from a guess about what this ministry prefers.

Exact weights for each city-pair in the index basket?
The brief never answers this, so a panel will. Whatever you decide, say it the same way twice.
Specific database schema to be used?
The brief never answers this, so a panel will. Whatever you decide, say it the same way twice.
Has any part of this been shown at a previous event, hackathon or college project?
The guidelines are explicit: your solution must not have appeared in any previous event or programme, of any sort. A recycled project is what a team under time pressure reaches for.

8 more— the ones a panel gets to if there is time

The brief asks for web scraping engine. How would you build that?
Decoded from SIH26056 itself — An automated Python tool that extracts airfare data from airline websites and travel aggregators while handling anti-bot measures. The brief asks for it by name.

The data

What the organisers attached, and what the brief assumes you can get.

Dataset from the organisers: Provided — open it
Does the brief need data?: Yes, and they gave it to you.

Also from MoSPI

Same organisation, same year. Reading two of theirs tells you more about what they care about than reading one.

Take this to an AI

Pick what you are about to do and copy the prompt. It carries the organisers' own wording, the constraints they never spell out, and an instruction not to invent requirements they never set.

Who has this problem, what already exists, and what you would have to find out.

# Context: India's Smart India Hackathon 2026

I am on a student team entering SIH 2026. Problem statement SIH26056, set by MoSPI.
Its official title, word for word: "Development of a Real-time Airfare Price Index for India through Automated Web Scraping of Airline and Online Travel Aggregator Portals for Augmentation of the Consumer Price Index (CPI)."
Theme: Smart Automation. Category: software.

In plain terms: A web platform that scrapes airline portals and travel sites to collect ticket prices, calculates a real-time airfare index, and displays trends on a dashboard for the NSO and RBI.

## The organisers' full description, verbatim

• Background The Consumer Price Index (CPI) released by the National Statistical Office (NSO), Ministry of Statistics and Programme Implementation (MoSPI), is the primary measure of retail inflation in India and is used by the Reserve Bank of India (RBI) for setting monetary policy under the flexible inflation-targeting framework. The current CPI framework, however, collects 'Transport and Communication' sub-group prices, including air travel fares, primarily through manual price-collection from a limited set of outlets and ticketing offices. With over 90% of domestic air tickets in India now sold online through airline websites and Online Travel Aggregators (OTAs) such as MakeMyTrip, Yatra, EaseMyTrip, Cleartrip, Ixigo and Goibibo, manual collection no longer captures the highly dynamic, route-specific, and time-sensitive pricing that Indian consumers actually face. Airfares in India follow dynamic pricing where the same sector can vary by 200-400% within a single day depending on advance-booking window, day-of-week, demand surges, festival seasons and fuel-price-linked surcharges. There is therefore an urgent need for an automated, scalable and high-frequency data-collection system that mirrors what a real Indian traveller pays. • Detailed Description The problem statement envisages development of an end-to-end software platform that automatically web-scrapes airfare data from major Indian airline websites (IndiGo, Air India, Air India Express, Akasa Air, SpiceJet) and leading OTAs, cleans and normalises the collected price quotes, and computes a Real-time Airfare Price Index (APIx) at daily, weekly and monthly frequencies. The system shall maintain a basket of representative city-pairs (such as DEL-BOM, DEL-BLR, BOM-BLR, DEL-CCU, BLR-HYD, MAA-DEL, etc.) selected on the basis of DGCA passenger-traffic data, and shall capture fares for multiple advance-purchase windows (T+1, T+7, T+15, T+30, T+45 days). Scraping must handle JavaScript-rendered pages, dynamic CAPTCHAs, anti-bot measures, IP rotation, and session management while remaining compliant with the robots.txt and terms of service of source websites, with appropriate rate-limiting and ethical-scraping safeguards. The collected raw quotes shall be passed through a data-cleaning pipeline that removes outliers, handles missing values, accounts for cancellations/sold-out flights, and separates base fare from taxes, user-development fee and convenience charges. The dashboard must visualise price trends, sector-wise heatmaps, lead-time elasticity curves, and provide an API that the NSO and RBI can consume. • Expected Solution A working software prototype consisting of (a) a robust, ethically-designed multi-source web-scraping engine using Python (Scrapy/Selenium/Playwright) capable of scheduled daily extraction from airline portals; (b) a cleaned and de-duplicated airfare database with metadata such as origin, destination, carrier, advance-purchase window, fare-class, base fare, taxes and total fare; (c) an index-construction module based on PSD given routes and weights; (d) a web-based interactive dashboard showing the daily Airfare Price Index. The solution must include documentation, automated testing, and demonstrate at least 30 days of back-tested results against publicly available DGCA monthly average-fare data.

## What the brief never says

- exact weights for each city-pair in the index basket
- specific database schema to be used
## Constraints that are not negotiable

- The judged build is a prototype demonstrated in roughly 36 hours by students, not a product.
- A jury evaluates it against this problem statement's own wording, not against general merit.
- We submit on sih.gov.in; the problem statement number and title above must match exactly.
- Your solution must not have appeared in any previous event or programme, of any sort.
- The organisers attached a dataset, so build against theirs rather than inventing one.

## What I want from you

1. Who actually has this problem in India, and what they do about it today.
2. What already exists — government systems, open-source projects, published research — that we should not rebuild.
3. For each item under 'what the brief never says', what the realistic answer is likely to be and how I could verify it.
4. The two or three things about this domain that a student team would get wrong without local knowledge.
## How to answer

- Everything above between quotation marks is the organisers' own wording. Treat it as the requirement.
- Do NOT invent requirements the brief does not state. If something matters and is not stated, say so and ask me, rather than assuming.
- Where you are inferring rather than reading, mark it as your inference.
- Do not guess what this ministry wants from its name. Its wording above is the only evidence.

---
Problem statement facts assembled by Wynit from MoSPI's published brief for SIH 2026.
The plain-English summary, the list of parts and the evaluator read are our interpretation of that text; the quoted title and the full description are theirs.

The government's original description (453 words)

• Background The Consumer Price Index (CPI) released by the National Statistical Office (NSO), Ministry of Statistics and Programme Implementation (MoSPI), is the primary measure of retail inflation in India and is used by the Reserve Bank of India (RBI) for setting monetary policy under the flexible inflation-targeting framework. The current CPI framework, however, collects 'Transport and Communication' sub-group prices, including air travel fares, primarily through manual price-collection from a limited set of outlets and ticketing offices. With over 90% of domestic air tickets in India now sold online through airline websites and Online Travel Aggregators (OTAs) such as MakeMyTrip, Yatra, EaseMyTrip, Cleartrip, Ixigo and Goibibo, manual collection no longer captures the highly dynamic, route-specific, and time-sensitive pricing that Indian consumers actually face. Airfares in India follow dynamic pricing where the same sector can vary by 200-400% within a single day depending on advance-booking window, day-of-week, demand surges, festival seasons and fuel-price-linked surcharges. There is therefore an urgent need for an automated, scalable and high-frequency data-collection system that mirrors what a real Indian traveller pays. • Detailed Description The problem statement envisages development of an end-to-end software platform that automatically web-scrapes airfare data from major Indian airline websites (IndiGo, Air India, Air India Express, Akasa Air, SpiceJet) and leading OTAs, cleans and normalises the collected price quotes, and computes a Real-time Airfare Price Index (APIx) at daily, weekly and monthly frequencies. The system shall maintain a basket of representative city-pairs (such as DEL-BOM, DEL-BLR, BOM-BLR, DEL-CCU, BLR-HYD, MAA-DEL, etc.) selected on the basis of DGCA passenger-traffic data, and shall capture fares for multiple advance-purchase windows (T+1, T+7, T+15, T+30, T+45 days). Scraping must handle JavaScript-rendered pages, dynamic CAPTCHAs, anti-bot measures, IP rotation, and session management while remaining compliant with the robots.txt and terms of service of source websites, with appropriate rate-limiting and ethical-scraping safeguards. The collected raw quotes shall be passed through a data-cleaning pipeline that removes outliers, handles missing values, accounts for cancellations/sold-out flights, and separates base fare from taxes, user-development fee and convenience charges. The dashboard must visualise price trends, sector-wise heatmaps, lead-time elasticity curves, and provide an API that the NSO and RBI can consume. • Expected Solution A working software prototype consisting of (a) a robust, ethically-designed multi-source web-scraping engine using Python (Scrapy/Selenium/Playwright) capable of scheduled daily extraction from airline portals; (b) a cleaned and de-duplicated airfare database with metadata such as origin, destination, carrier, advance-purchase window, fare-class, base fare, taxes and total fare; (c) an index-construction module based on PSD given routes and weights; (d) a web-based interactive dashboard showing the daily Airfare Price Index. The solution must include documentation, automated testing, and demonstrate at least 30 days of back-tested results against publicly available DGCA monthly average-fare data.