Many electricity, gas, water, and heat meters required manual reading by technicians, generating high costs and significant workload. The COVID-19 pandemic further complicated the situation by restricting access to residential properties. Replacing meters with remote IoT models would have involved millions in costs and required intervention in customers' infrastructure.

Escola designed a mobile app enabling Innogy field workers to remotely read meters using a smartphone camera. After photographing a meter, the data is processed by an OCR algorithm supported by Machine Learning and automatically added to the customer's account. The algorithm was trained on over 40 different meter types — mechanical, digital, and radio — and works even in poor lighting conditions or when meter displays are dirty.
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The project included client workshops, the creation of a complete system architecture, a development roadmap, and integration with Innogy's existing systems. The app was tested on multiple smartphone models and operating systems, ensuring near-flawless performance in everyday conditions.