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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM67796
Volume:
10 |
10 |
Oct 2026
Pages:
1-5
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

Electronic & Telecommunication Engineering.
JSMP Bhivrabai Sawant Polytechnic
Electronic & Telecommunication Engineering.
JSMP Bhivrabai Sawant Polytechnic
Electronic & Telecommunication Engineering.
JSMP Bhivrabai Sawant Polytechnic
Electronic & Telecommunication Engineering.
JSMP Bhivrabai Sawant Polytechnic
Electronic & Telecommunication Engineering.
JSMP Bhivrabai Sawant Polytechnic
NexusGuard AI is an Artificial Intelligence (AI) and Internet of Things (IoT)-based integrated smart infrastructure system designed to improve safety, monitoring, emergency response, and energy efficiency in college campuses. The proposed system combines multiple independent campus facilities such as surveillance, environmental monitoring, emergency warning, smart lighting, and communication into a unified smart pole. An ESP32 microcontroller collects sensor data and performs device-level control, while a Raspberry Pi 4 processes camera data for AI-based object detection and event analysis. The system incorporates an AI camera, PIR motion sensor, smoke and gas sensors, flame sensor, temperature and humidity sensor, air-quality sensor, sound sensor, LDR, and emergency SOS button. Abnormal conditions can trigger a siren, speaker, warning lighting, display, and remote notification. Sensor and event data are communicated using Wi-Fi and MQTT, stored through Firebase, and presented on a dashboard or mobile application. Solar power with battery backup supports autonomous operation. The proposed system provides a scalable approach for campus safety, environmental monitoring, energy management, and future smart-campus integration.
KEYWORDS
NexusGuard AI presents an integrated approach to campus safety and sustainability by combining artificial intelligence, Internet of Things technologies, embedded controllers, environmental sensors, camera-based surveillance, smart lighting, emergency response, cloud monitoring, and renewable power into a unified smart-pole architecture. The ESP32 functions as the main sensor and control controller, while the Raspberry Pi 4 performs AI-based camera processing. A collection of sensors provides information about movement, smoke, gases, flame, temperature, humidity, sound, and ambient light, while the actuator section enables local warning and control through LEDs, siren or buzzer, speaker, OLED display, and relay devices. Wi-Fi and MQTT provide network communication, Firebase provides real-time cloud management, and the dashboard or mobile application allows remote monitoring. Solar power, battery storage, and DC-DC conversion support autonomous operation. Overall, the proposed architecture aims to overcome the limitations of fragmented campus systems by providing a centralized, intelligent, scalable, and energy-conscious infrastructure for safety and sustainability.
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Publication Date
10/10/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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