Contact person: Business Client

Phone:Show

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Location: Cape Town, South Africa

Budget: Recommended by industry experts

Time to start: As soon as possible

Project description:
"I need a full-stack developer or small team to turn my concept for an AI-driven solar assistant into a production-ready product. The app must forecast solar output, flag performance issues, and actively suggest ways to shift or reduce consumption so users squeeze the most value from every kilowatt.

Scope
• Two user-facing clients: a native Android build (Kotlin or Flutter are fine) and a responsive web interface (React, Vue, or similar). Both should share one code-base for business logic where practical.
• A cloud backend that ingests live weather feeds and energy-consumption readings, then runs machine-learning models to deliver:
– real-time performance dashboards
– short-term generation forecasts
– predictive maintenance alerts
– optimisation tips based on usage profiles
• Secure APIs for data exchange with external meters and publicly available weather endpoints.

Key data sources
• Weather data (hourly and forecast)
• Smart-meter or inverter energy-consumption data

Deliverables
1. Android APK and Play-ready bundle
2. Deployed web app with CI/CD script
3. Trained prediction models (Python/TensorFlow or equivalent) with reproducible notebooks
4. REST or GraphQL API documentation
5. Setup guide and brief user manual

Acceptance criteria
• Forecast MAE ≤ 7 % on test-week data
• Dashboard refresh ≤ 5 s on 4G connection
• End-to-end encryption for user data in transit and at rest
• No critical issues in a 48-hour beta run on both platforms

If this sounds like a challenge you can tackle, please outline your proposed architecture, core tech stack, and a milestone schedule in your bid." (client-provided description)