IntelliGuard: IoT-Enabled Autonomous Spybot Intelligence for Real-Time Surveillance in Next-Generation Security Applications

📢 New Research Publication Release

I am pleased to announce the publication of our research paper titled “IntelliGuard: IoT-Enabled Autonomous Spybot Intelligence for Real-Time Surveillance in Next-Generation Security Applications”, officially published as an Open Access conference paper in the Proceedings of the 2nd Symposium on Smart, Sustainable, and Secure Internet of Things (S4IoT 2025), held in Doha, Kuwait 🇰🇼.

The paper appears in Springer’s prestigious Lecture Notes in Electrical Engineering (LNEE), Volume 1513, and was published online on 01 February 2026 by Springer, Singapore.

🔍 Research Overview

IntelliGuard presents an IoT-enabled autonomous surveillance robot designed for real-time monitoring in next-generation military and security applications. Built on an ESP32-based architecture, the system integrates camera streaming, motor-driven navigation, radar, and ultrasonic sensors to enable autonomous mobility, obstacle detection, and secure remote surveillance. Field testing demonstrates reliable performance in low-interference environments with minimal response latency. The study lays a strong foundation for future advancements in IoT-connected robotic surveillance systems, emphasizing scalability, cost-effectiveness, and secure communication.

👥 Authors

Dhruv Dhayal, Pratham Aggarwal, Manzoor Ansari

📚 Publication Details

Conference: S4IoT 2025 – Symposium on Smart, Secure, and Sustainable Internet of Things

Series: Lecture Notes in Electrical Engineering (LNEE, Vol. 1513)

Pages: 163–173

Publisher: Springer, Singapore

Access: Fully Open Access

🔗 Links

DOI: https://doi.org/10.1007/978-981-95-5136-1_16

Open Access PDF: https://link.springer.com/chapter/10.1007/978-981-95-5136-1_16

Shareable Link: https://rdcu.be/e2MoR

This publication reflects our continued commitment to research, innovation, and open science, contributing to the advancement of IoT-based intelligent security systems.

Confrence

📘 Literature Review Summary (for GitHub Release Tag)
The evolution of IoT and cloud computing technologies has enabled transformative changes in real-time rescue and surveillance systems. In the context of public safety and emergency response, numerous studies highlight the efficiency and intelligence brought by these technologies when integrated with AI and decision-making algorithms. Sinha et al. (2019) present a foundational framework by applying Task-Technology Fit theory to IoT-based disaster management, proving that IoT devices can effectively collect, transmit, and contextualize data in real time to support critical rescue missions during natural disasters. Their work emphasizes the role of cloud-enabled infrastructure in handling vast sensor data, which is directly aligned with the architecture of IntelliGuard Ver. 2.

Complementing this, Roy et al. (2022) explore a multi-robot system integrated with IoT and secured via cloud computation for coordinated rescue tasks. Their model particularly focuses on ensuring communication and data security, which is essential for remote operations like pipeline inspections and borewell rescues, as envisioned in IntelliGuard. Similarly, Sood et al. (2018) propose a Fog-IoT architecture for smart flood monitoring, where latency-sensitive data is processed locally while non-critical data is offloaded to the cloud. This hybrid architecture is closely aligned with IntelliGuard’s goal of radar-based obstacle detection and real-time decision-making at the edge.

Further, Padmaavathy et al. (2022) stress the importance of AI integration in IoT-cloud systems, proposing models where intelligent anomaly detection and predictive analytics can secure and optimize real-time data communication in critical operations. Their security-focused perspective is instrumental in preventing system breaches in surveillance applications. Finally, the IntelliGuard concept by Pandey and Bhatt (2023) lays a direct foundation for your project by integrating AI-based cyber-defense strategies with IoT surveillance bots, offering real-world applications for safeguarding sensitive zones.

In summary, these scholarly works collectively support the development of IntelliGuard Ver. 2 by validating the use of IoT, cloud infrastructure, AI-based analytics, and autonomous systems in public safety scenarios. They reinforce the viability of building a robust, real-time, and intelligent rescue monitoring bot equipped with radar, camera sensors, and private IP streaming for inaccessible or hazardous environments like borewells, underground pipelines, and mining tunnels.