National Weather Big Data Analytics Platform
“This project is about building a smart system that gathers weather reports from social media, news, and public data to track disasters in real-time. It uses AI to filter out fake news and automatically maps weather events like floods or heatwaves so officials can respond faster.”
Deconstructed Problem Blueprint
WHAT TO BUILD?
A scalable Big Data Analytics Platform with a web-based dashboard for real-time weather event monitoring and verification.
WHO IS IT FOR?
Primary: India Meteorological Department (IMD) officials and disaster management teams. Secondary: General public and emergency responders.
WHY DOES IT EXIST?
Current systems rely heavily on official weather stations which are sparse. Crowdsourced data is abundant but noisy, unverified, and scattered across platforms, making it difficult for authorities to get a ground-truth picture of localized disasters.
INPUT → PROCESS → OUTPUT ARCHITECTURE PIPELINE
Social media feeds (X/Instagram API), public weather APIs (OpenWeather/IMD), user-submitted reports via mobile app/web, and geotagged multimedia content.
Real-time ingestion pipelines (Kafka/Spark), AI-based fake news detection (NLP/LLM), image/video analysis for event verification, and deduplication algorithms.
Interactive GIS-based dashboard, automated event categorization, verification status reports, and heatmaps for disaster impact.
CONSTRAINTS
- Must handle high-velocity data streams without latency.
- Must comply with data privacy and social media API usage policies.
- Must operate in low-bandwidth scenarios for remote field reports.
- Must support multi-lingual text processing for regional Indian languages.
JURY METRICS
- Accuracy of fake news detection (Precision/Recall).
- System latency from event occurrence to dashboard update.
- Dashboard UI/UX responsiveness and ease of data filtering.
- Scalability of the data ingestion pipeline.
CORE BOTTLENECK
The 'Verification Engine'—distinguishing between a genuine disaster report and a viral fake post or old recycled video is the hardest technical hurdle.
Why You Should Choose This PS (Pros)
- High social impact with direct alignment to national disaster management goals.
- Clear, modular scope allows for incremental development.
- Strong potential for integration with existing government portals like Bhuvan.
Challenges & Risks to Watch (Cons)
- Social media API costs and strict rate limits.
- High complexity in building a robust, real-time data pipeline within 36 hours.
- Risk of 'garbage in, garbage out' if data cleaning is not prioritized.
Recommended Tech Stack & Grand Finale Features
Killer Features to Impress the SIH Jury
View Official SIH 2026 Portal Raw Text▼
Design and develop a scalable National Weather Big Data Analytics Platform capable of collecting and processing real-time weather-related information for India from multiple internet-based sources including social media platforms, public datasets, websites, APIs, and citizen reports. The platform should automatically collect weather related posts and information tagged with #IMD and other relevant weather hashtags, along with metadata such as date & time, city, state, GPS location, photos, videos, and event category, and store the information in a centralized database.
The system should leverage big data technologies and open-source tools to support large-scale real-time data ingestion, processing, storage, and visualization.
Participants are encouraged to use machine learning and AI-based techniques to identify fake or misleading reports, verify untrusted sources, remove duplicate entries, and automatically categorize weather events such as rainfall, thunderstorms, flooding, heatwaves, fog, dust storms, and strong winds.
Develop a web-based dashboard and Admin Panel for monitoring and analysing collected data with features including: