B

Customized Disaster Evacuation Plan for Parents

2.85

Derivation Chain

Step 1 Public disaster safety data opening
→
Step 2 Increased caregiving responsibility for parents among 40-60s
→
Step 3 Lack of disaster evacuation plans for elderly parents

Problem

A 50-something office worker living apart from parents in their 70s-80s has not prepared evacuation routes, nearby shelter locations, or an emergency contact system for disasters such as earthquakes, fires, wildfires, and heavy rain. Although the government's civil defense shelter information exists, it is not customized to the parents' residence, and there is no tool to create an evacuation plan that accounts for the parents' limited mobility. In actual disasters, they may lose contact or not know shelter locations.

Solution

On the web, users input the parents' home address and mobility status, and the service automatically calculates the three nearest shelters, walking routes, and estimated travel time, generating a customized evacuation plan. Key features: (1) nearest shelter matching based on home address with slope-aware routes, (2) one-click sharing to parents' smartphones (shelter map + emergency contacts), (3) disaster-type-specific action checklists (earthquake/fire/flood).

Target: Aged 48-60, living apart from parents aged 70+, parents in good health but needing emergency preparedness.
Revenue Model: Basic evacuation plan is free. Family emergency contact auto-update service at 1,900 KRW/month (approximately $1.43). Also B2G sales to local governments.
Ecosystem Role: Consumer
MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty
3.0/5
U Urgency
2.0/5
M Market
2.0/5
R Realizability
4.0/5
V Validation
2.0/5
NUMR-V Scoring System
N Novelty1-5How uncommon the service is in market context.
U Urgency1-5How urgently users need this problem solved now.
M Market1-5Market size and growth potential from proxy indicators.
R Realizability1-5Buildability for a small team with realistic constraints.
V Validation1-5Validation signal quality from competition and demand data.
Each dimension is scored 1-5 and weighted into grade S/A/B/C/D.
N=.15 U=.20 M=.15 R=.30 V=.20

Feasibility (71%)

Tech Complexity
32.0/40
Data Availability
19.2/25
MVP Timeline
20.0/20
API Bonus
0.0/15
Feasibility Breakdown
Tech Complexity/ 40Difficulty of core implementation stack.
Data Availability/ 25Practical availability and cost of required data.
MVP Timeline/ 20Expected time to ship a usable MVP.
API Bonus/ 15Bonus for viable public API leverage.
Total 100 points; below 50% is filtered out.

Market Validation (50/100)

Competition
8.0/20
Market Demand
6.2/20
Timing
14.0/20
Revenue Signals
7.5/15
Pick-Axe Fit
7.5/15
Solo Buildability
7.0/10
Validation Breakdown
Competition/ 20Signal quality from competitor landscape.
Market Demand/ 20Demand proxies from search and mention patterns.
Timing/ 20Fit with current shifts in tech, behavior, and regulation.
Revenue Signals/ 15Reference evidence for monetization viability.
Pick-Axe Fit/ 15How well the concept serves participants in a trend.
Solo Buildability/ 10Practicality for lean-team implementation.
Total 100 points; below 50 is filtered out.

Technical Requirements

Frontend [medium] Backend [low]
Dashboard