SWRM.IO
Safety. Automated.
Avalanches
Rocks
Unskilled skiers
Bad weather
Bad snow conditions
Trees
Crashing into other skiers
The Problem
Value Proposition
We employ drones coupled with advanced machine vision algorithms to improve response times for accidents, find lost people, predict avalanches and denote area safety in mountains
Features
- Skier localization through visuals/GPS (thru app or ski pass) --- to improve response times
- Designation of high risk areas (thru vision API)
- Pipeline of information from safety personal to customer -- dashboard and app
Architecture
-
What data is being ingested --> from where and how
- Location data (latitude/longitude)
- Weather data
- Drone imaging data
-
Prioritization of data based on weather conditions
- Localization thru GPS and visuals
- Localization thru just GPS
- Vision api - Microsoft Cognitive Service API
- Hardware - industrial grade drones
Drone data of slopes in the valley
Categorize the off-slope areas by level of danger
Real-time skier location
Expansion to resort customer app
Key Stats
€ 10.000 per rescue
Vail resorts reinvested $113 million (2016)
50% reinvest is standard
360m skiers in world wide
2132 resorts worldwide
80% of biggest resorts in Alps (49)
Winter & Summer season (skiing, hiking)
US & Alps biggest
Beachhead market
Alps
Austria, France, Italy, Switzerland
155m skiers in the Alps
767 resorts
Alps region has same safety regulations for ski resorts
+3000 rescues in alps
Small area: 298,128km²
25 billion annual turnover from winter season
Big Data Architecture
Drone data of slopes in the valley
Categorize the off-slope areas by level of danger
Real-time skier location
Expansion to resort customer app
SWRM
Startup semifinal
By laurenstc
Startup semifinal
startup semi-final deck mbd
- 529