SIH26056: Development of a Real-time Airfare Price Index for India through Automated Web S — SIH 2026 | Wynit

SIH26056: Development of a Real-time Airfare Price Index for India through Automated Web S — SIH 2026 | Wynit

What they'll ask you

11

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 morethe 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 brief asks for data cleaning pipeline. How would you build that?
Decoded from SIH26056 itself: A module that processes raw price quotes, removes outliers, handles missing values, and separates base fares from taxes and fees. The brief asks for it by name.
The brief asks for index construction module. How would you build that?
Decoded from SIH26056 itself: A calculation engine that computes the Airfare Price Index across representative city-pairs and advance-purchase windows. The brief asks for it by name.
The brief asks for interactive dashboard. How would you build that?
Decoded from SIH26056 itself: A web interface that visualises price trends, sector-wise heatmaps, and lead-time elasticity curves. The brief asks for it by name.
The brief asks for api and export. How would you build that?
Decoded from SIH26056 itself: An endpoint that allows external users like the NSO and RBI to consume the processed index data. The brief asks for it by name.
Why not use what already exists? Name the closest thing to this that is already running.
A team that has not named the alternative themselves is answering this for the first time in the room.
Which single thing will you demonstrate end to end, start to finish, with nothing skipped?
Ours, not a rule: a narrow thing that fully works survives questioning better than a broad thing that half works. If nobody on the team can name it, that is the finding.
Show me this working: 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.
This is the evaluator read for your problem statement, decoded from the brief's own wording.

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.