Dr. N. Srinivasa Rao,Swamulapally Ravindra,Konda Archana,Valleti Venkata Lakshmi,Veeramsetti Manikanta,Chetla Saikiran 03 03 The increasing demand for efficient resource management and fair billing mechanisms in shared living spaces hostels rental properties and coworking environments has necessitated the development of automated payforuse systems Traditional flatrate billing models often lead to inequitable cost distribution and resource wastage as users lack incentives for conservation This paper presents an RFIDbased Resource Billing System a comprehensive IoTenabled payforuse platform that tracks individual consumption of resources electricity water TV fans appliances and generates usagebased bills with integrated data analytics The system comprises three integrated components 1 an ESP8266based hardware module with RFID readers MFRC522 and relay circuits connected to resource outlets enabling taptostart and taptostop usage tracking with 998 accuracy 5 2 a Firebase Realtime Database cloud infrastructure that maintains user profiles resource rates usage sessions billing records and synchronization across multiple devices with 150ms average latency 6 and 3 a Python Tkinter analytics application that performs comprehensive data analysis including usage pattern recognition peak demand forecasting anomaly detection and customizable report generation daily weekly monthly yearly The system implements a complete workflow user registration with RFID card assignment resource selection via RFID tap realtime usage tracking with session management automatic billing based on configurable rates 012kWh for electricity 005gallon for water 050hour for TV etc and payment processing The ESP8266 firmware written in Arduino C maintains persistent connection to Firebase using REST APIs with watchdog timers ensuring 999 uptimeThe Python analytics application utilizes pandas for data manipulation matplotlibseaborn for visualization scikitlearn for predictive modeling and tkinter for the graphical user interface Experimental deployment across 50 rooms in a university hostel over 6 months generated 25000 usage sessions demonstrating 34 reduction in overall resource consumption compared to flatrate billing 28 cost savings for lowusage users and 975 user satisfaction The analytics module identified peak usage patterns evenings 610 PM accounting for 45 of electricity consumption detected anomalous usage events 15 cases of potential theftmisuse and forecasted demand with 92 accuracy using SARIMA models The system supports up to 500 concurrent devices per Firebase instance with daily backups and GDPRcompliant data retention policies This work represents the first integrated RFIDbased payforuse system combining realtime IoT tracking with advanced analytics demonstrating significant potential for equitable resource billing and consumption optimization Copyright (c) Journal of Science Engineering Technology and Management Science. All rights reserved 2026