1 Department of Computer Science Engineering Government Polytechnic Kudligi Karnataka, India.
2 Department of Computer Science Engineering, Government Polytechnic Harihar, Karnataka, India.
Research Article
World Journal of Advanced Research and Reviews, 2022, 15(03), 513-525
Article DOI: 10.30574/wjarr.2022.15.3.0724
Received on 13 July 2022; 25 September 2022; accepted on 29 September 2022
The increasing demand for intelligent surveillance systems has led to the integration of Internet of Things (IoT) technology with advanced image processing techniques to enhance security applications. This paper presents a novel framework that combines IoT-enabled devices with adaptive image processing, leveraging the power of edge computing and machine learning to optimize real-time analysis of visual data. Traditional surveillance systems often face limitations such as high latency, bandwidth constraints, and inadequate adaptability to dynamic environments. Our proposed solution addresses these challenges by processing data closer to the source, reducing latency and bandwidth usage while maintaining high processing accuracy. The framework integrates adaptive algorithms for dynamic resolution adjustment, context-aware object detection, and real-time anomaly detection, allowing the system to intelligently adjust based on scene complexity, environmental conditions, and available computational resources. Additionally, the use of machine learning techniques enhances the system’s ability to learn from new patterns and adapt to evolving security threats. Experimental evaluations demonstrate the proposed system’s superior performance in terms of object detection accuracy, processing speed, and energy efficiency compared to traditional centralized surveillance systems. This paper also discusses the implementation of secure communication protocols and privacy-preserving techniques to ensure data security in IoT environments. The proposed framework offers a scalable and flexible solution, making it suitable for a wide range of security applications, from public spaces to private facilities. Future work will focus on improving the system's robustness and extending its capabilities for large-scale deployments.
Internet of Things; Smart surveillance; Adaptive image processing; Edge computing; Machine learning
Preview Article PDF
Channappa A, Praveena K B and Durugappa Patrer. IoT-enabled smart surveillance: Adaptive image processing for security applications. World Journal of Advanced Research and Reviews, 2022, 15(3), 513-525. Article DOI: https://doi.org/10.30574/wjarr.2022.15.3.0724