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Nasir Nasir-Ameen
Notes

Intelligent PV Monitoring and Power Efficiency Prediction

The mobile application and the hardware logger were different contributions

Preserving individual ownership boundaries in an IoT and machine-learning group project.
5 min read

The photovoltaic project combined an IoT logger, an Android monitoring application and a prediction workflow. The integrated system was group work, but the parts were not interchangeable.

My main contribution was the Xamarin.Forms GreenHouse Logger application and the predictive-model workflow. The hardware logger was built by my project partner.

Why this belongs in the technical description

The mobile application connected over the logger's Wi-Fi network, visualised inverter measurements and supported data export. The modelling workflow cleaned and normalised the recorded dataset before training the reported network.

Naming those boundaries makes the project easier to evaluate. It preserves the integrated nature of the system without turning a partner's hardware implementation into my individual claim.