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@article{199130,
        author = {Dr. GK ABANI KUMAR DASH and ANKITA DAS and A.S. DEEPALI and HEMANGINI DALEI and Dr. Uttam Panda},
        title = {FROM EFFECTIVENESS TO CREDIBILITY: AN ANALYSIS OF AI- POWERED SECURE AND ENERGY-AWARE IOT SYSTEMS},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {13153-13159},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=199130},
        abstract = {The Internet of Things (IoT) has become a fundamental component of modern society due to its extensive connectivity and communication capabilities. However, the lack of standardisation in IoT systems has resulted in significant challenges related to security, privacy, and high energy consumption. Artificial intelligence (AI) techniques, including machine learning (ML), deep learning (DL), and reinforcement learning (RL), have shown significant potential in addressing these challenges through the implementation of intrusion detection systems, authentication mechanisms, privacy-preserving techniques, and energy-aware routing strategies. This survey reviews and analyses existing research works that employ AI-based approaches to enhance IoT security requirements, mitigate various threats and attacks, and optimise routing mechanisms to extend the operational lifetime of remotely connected IoT devices in wireless sensor networks (WSNs).},
        keywords = {Internet of Things (IoT), Wireless Sensor Networks (WSNs), Artificial Intelligence (AI), Deep Reinforcement Learning (DRL), Energy Efficiency, Routing Optimisation, Network Longevity, Intrusion Detection, Privacy Preservation, 6G Connectivity.},
        month = {April},
        }