Real Time Utility Bill Analytics with Machine Learning:A Mobile Solution For Escom Prepaid Users in Malawi

This project presents the development of a mobile application, "RealTime Utility Bill Analytics with Machine Learning," designed to enhance electricity management for prepaid users of the Electricity Supply Corporation of Malawi (ESCOM). In Malawi, where prepaid systems dominate and challenges like inaccessible billing, unpredictable usage, and delayed infrastructure responses persist, this app provides a unified platform for real-time bill viewing, payment processing, consumption analytics, budgeting, and issue reporting.
Key features include: seamless integration with ESCOM's API for retrieving current and historical bills; machine learning-driven predictions of future usage patterns to aid informed decision-making; proactive notifications for low electricity levels (e.g., below 20 kWh) and personalized energy-saving tips; a geolocation-enhanced module for reporting infrastructure issues like faulty meters or outages; and budgeting tools with alerts (e.g., at 80% of a 150 kWh monthly limit). Built using Flutter for cross-platform compatibility (Android/iOS), the app employs a green-themed interface and plans for SMS/USSD support to ensure accessibility in low-tech rural areas.
A literature review highlights gaps in existing utility apps, such as limited predictive analytics and integration, which this solution addresses to potentially reduce consumption by 5-10% through user awareness. The project underscores the role of mobile technology in promoting energy efficiency and financial inclusion in developing regions.