AI–Tourism Hackathon
A 24-hour hackathon applying artificial intelligence to the real problems of tourism in Uttarakhand
Hosted By
Department of Hospitality Management
Technology Business Incubator at Graphic Era Deemed to be University
What problem is this actually solving?
Uttarakhand's tourism economy is large and mostly undigitised. Homestay owners keep guest records on paper. Char Dham registrations spike every May with no forecasting behind them. State policy has created thousands of registered homestays that still don't show up in a single online search. And on high-altitude routes, a missed check-in can go unnoticed for hours.
This hackathon hands those specific problems to student teams for 24 hours. The only rule: whatever gets built has to use AI to address something a real homestay owner, trekker, or tourism office is dealing with right now, not a hypothetical.
Why every team needs a Hospitality Management student?
A team of only computer science students can ship code fast, but they won't know why Form C compliance trips up nearly every unregistered homestay, or what actually slows down a booking reply in Munsyari. A team of only Hospitality Management students knows the operational pain in detail but can't build the tool.
So the rule is fixed: Technical teams are limited to exactly 3 students. We will allocate one Hospitality Management student to each technical team to provide crucial domain expertise.
Every submission has to run. Concepts and slide decks without a working build are not judged.
5 Specialized Tracks
Tackle challenges spanning every corner of the tourism ecosystem.
Demand Forecasting & Revenue
Guest Experience & Feedback
Food & Beverage Operations
Resource Efficiency & Sustainability
Workforce Management
The 18 problem statements
Demand Forecasting & Revenue
Hotel demand in Uttarakhand swings violently and predictably, yet almost no property forecasts it. May and June fill on Char Dham and summer holidays; February empties. Managers order supplies, roster staff and set rates on last week's occupancy and a feeling about the month ahead. The cost of being wrong runs both ways — a property caught short in peak turns away business it cannot recover, and one that over-provisions in lean bleeds cash through the quiet months.
Predict hotel occupancy for the next day, week and month using historical occupancy, season, weekends, holidays, festivals, tourist arrivals, weather and local events. Alert managers to expected high- and low-demand periods before they arrive, and recommend appropriate operational strategies for each — purchasing, staffing, rate posture and promotion.
Multi-horizon time-series forecasting with calendar, weather and event features; handling short and irregular history typical of a small property; translating a forecast into an operational recommendation rather than a number.
Forecast accuracy against actual occupancy · advance warning lead time · reduction in emergency purchasing and last-minute staffing · occupancy and revenue variance against plan.
Schedule
Check-in and Inauguration
Build begins
Build ends
Valdictory Ceremony
Prizes
| Position | Award |
|---|---|
| First | ₹30,000 |
| Second | ₹20,000 |
| Third | ₹10,000 |
| Best in track (5 awards) | Certificate of Appreciation |
| All finalists | Certificate of Participation |
Questions people will actually ask
Registration & Team Formation
Choose your domain below. Registration closes 20 September, and Submission closes 23 September.
Technical Domain
- Requirement: Teams of exactly 3 students from any domain (e.g. B.Tech, BCA).
- We will allocate one HM student to your team to provide domain expertise.
- You must join the Technical WhatsApp group for updates.
Hospitality Management
- Requirement: Solo entries only.
- We will integrate you into a technical team to provide critical domain expertise.
- You must join the HM WhatsApp group for updates.
