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@article{207435,
        author = {Aravind T and Avinash Dubey and Aryan and Chirayu N Hudar},
        title = {Dynamic Spectrum Access and Autonomous Channel Allocation in Wireless Sensor Networks},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {3},
        pages = {1295-1301},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=207435},
        abstract = {The 2.4 GHz ISM band has become critically saturated. The 2.4 GHz range is subject to severe overcrowding issues. With billions of Internet of Things (IoT) devices sending signals at once, the spectrum space becomes prone to collisions constantly. Because of this, static frequency assignment fails. The initial CR and DSA models were developed under the assumptions about large macro-cellular network configurations with servers located centrally. Forcing such an approach on the edge nodes with energy constraints proves to be inefficient, leading to overheating and high processing lags. In this research, we propose another solution by moving from simple thresholding to distributed machine learning on the edge. Specifically, we will look into what is possible when training and utilizing lightweight classification algorithms, such as Random Forest, on energy-constrained microcontrollers. This paper intends to reduce the higher than desirable number of false alarms generated by affordable sensors. Moreover, we deal with MAC-layer latency issues. Avoiding Wi-Fi association overheads, we showcase how intelligent secondary nodes can switch channels in microseconds without the need for any connections},
        keywords = {Cognitive Radio, Dynamic Spectrum Access, Edge Computing, Machine Learning, Media Access Control, Wireless Sensor Networks.},
        month = {August},
        }