Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{177911,
        author = {Jay Ashokkumar Soliya and Amarsinh Bhimrao Varpe and Anil Patel},
        title = {Problem Solving with Intelligent Intrusion Detection Using Deep Learning and Iot: A Review},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {2912-2917},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=177911},
        abstract = {This study aims to develop an intelligent intrusion detection and alert system by utilising machine learning and internet of things components. The setup uses a PIR sensor and an Arduino Uno to detect motion. Motion events are recorded after data has been collected and preprocessed. Machine learning techniques that recognise motion patterns, such as Random Forest and Decision Tree, are used to distinguish between humans and animals. When the system senses a human presence, it notifies the SIM900A module. Using a camera module in conjunction with a cloud-based server for Deep Learning analysis is an add-on that may be utilised to increase detection accuracy. This approach uses real-time data processing and machine learning to provide a robust intrusion detection solution.},
        keywords = {Intrusion Detection, IoT, Machine Learning, PIR Sensor, Notification Setup, SIM900A Module, Ultrasonic Sensor, IR Sensor, Arduino Uno, OV7670 Camera.},
        month = {May},
        }