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

  1. Skier localization through visuals/GPS (thru app or ski pass) --- to improve response times
  2. Designation of high risk areas (thru vision API)
  3. Pipeline of information from safety personal to customer -- dashboard and app

Architecture

  1. What data is being ingested --> from where and how
    1. Location data (latitude/longitude)
    2. Weather data
    3. Drone imaging data
  2. Prioritization of data based on weather conditions
    1. Localization thru GPS and visuals
    2. Localization thru just GPS
  3. Vision api - Microsoft Cognitive Service API
  4. 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

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