농산물 출하시기·가격예측 SaaS (기상·작황 데이터 결합 의사결정 도구 부재)
농업 기상 서비스(aWhere, Climavision) — 필지 단위 마이크로 알림 특화
스마트팜 노코드 제어 대시보드 (IoT 센서·자동화 조작 병목의 확장)
Farmers must check pest forecasts from the Rural Development Administration, weather alerts from the Korea Meteorological Administration, and provincial agricultural technology center notices on separate sites and apps, making it difficult to determine if they apply to their own fields. Missing the optimal spraying window by just one day can spread damage 3-5 times, resulting in annual losses of several million won (approx. $1,500–$3,750).
When a farmer registers their field address and crop type, the service combines Korea Meteorological Administration API, pest forecast data, and satellite NDVI to calculate a daily risk score for their specific field, sending spraying timing alerts via KakaoTalk notification. It also recommends pesticides and application rates when risk is high.
| N Novelty | 1-5 | How uncommon the service is in market context. |
| U Urgency | 1-5 | How urgently users need this problem solved now. |
| M Market | 1-5 | Market size and growth potential from proxy indicators. |
| R Realizability | 1-5 | Buildability for a small team with realistic constraints. |
| V Validation | 1-5 | Validation signal quality from competition and demand data. |
| Tech Complexity | / 40 | Difficulty of core implementation stack. |
| Data Availability | / 25 | Practical availability and cost of required data. |
| MVP Timeline | / 20 | Expected time to ship a usable MVP. |
| API Bonus | / 15 | Bonus for viable public API leverage. |
| Competition | / 20 | Signal quality from competitor landscape. |
| Market Demand | / 20 | Demand proxies from search and mention patterns. |
| Timing | / 20 | Fit with current shifts in tech, behavior, and regulation. |
| Revenue Signals | / 15 | Reference evidence for monetization viability. |
| Pick-Axe Fit | / 15 | How well the concept serves participants in a trend. |
| Solo Buildability | / 10 | Practicality for lean-team implementation. |