IoT-Cloud Smart Campuses Enabling Real-Time Intelligent Resource Automation

Abstract

This study proposes an IoT-based smart campus framework integrating Arduino microcontrollers, cloud services, and sensor networks to automate traffic control, adaptive lighting, smart rooms, and irrigation systems. The system aims to transform traditional campus management by enhancing operational efficiency, sustainability, and safety through real-time data analytics.

Objectives: Use of Arduino microcontrollers to automate processes in campus and remote monitoring over cloud through MQTT protocols to optimize resource utilization.

Method: Sensor networks (motion, gas, RFID), microcontrollers (Arduino Mega, NodeMCU) and wireless staff (ESP8266) was applied to collect real-time data. Cloud integration (CloudMQTT) and REST APIs enabled centralized control. Automated algorithms adjust lighting, HVAC, traffic signals, and irrigation based on sensor feedback.

Results: Some key metrics are as follows: 40% in energy savings in lighting, 35% global water savings towards irrigation, 98.7% in RFID accuracy and 40% decrease on global traffic wait time (on peak hours).

Conclusion: The IoT substantially enhances campus management. Future work will combine AI with air quality sensors