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@article{186524,
        author = {Prof. V.P. Shinde and Mr. Om G. Roman and Mr. Bhagwat Lipne and Mr Shreyas S. Sandhbhor and Mr. Shivam Samratkar},
        title = {Wi-Fi Through Wall Human Motion Detection Using Wi-Fi & Raspberry Pi},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {6},
        pages = {982-985},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=186524},
        abstract = {Wi-Fi-based human motion detection is becoming a powerful and non-intrusive method for identifying and tracking human activities, even through walls or obstacles. This technique relies on subtle changes in Wi-Fi signals specifically Channel State Information (CSI) and Received Signal Strength Indicator (RSSI) to interpret movement patterns using affordable, commercial Wi-Fi devices. This review highlights recent advancements in through-wall human sensing and introduces a low-cost system built with Wi-Fi modules and a Raspberry Pi for device-free motion detection. It examines leading research efforts aimed at improving detection accuracy, signal stability, and adaptability to different environments. The paper also discusses how deep learning and IoT integration can enable real-time, intelligent human presence recognition with minimal hardware complexity.},
        keywords = {Wi-Fi Sensing, Channel State Information (CSI), Human Motion Detection, Raspberry Pi, Through-Wall Sensing, IoT, Deep Learning.},
        month = {November},
        }