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@article{178295,
        author = {Raghavendra Prasad H D and Santosh Kumar Sah and Shashwat Singh and Aashish Gurung},
        title = {Advanced Sensor-Based Systems for Real-Time Landslide Detection, Monitoring, and Early Warning in Vulnerable Regions of India},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {4442-4450},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=178295},
        abstract = {Landslides pose serious risks to life, property, and infrastructure in India’s mountainous regions. To address these risks, advanced sensor-based systems are being employed for real-time detection and early warning. This study evaluates various sensor technologies to enhance landslide monitoring accuracy. MEMS-based IMUs—Pixhawk, MPU6050, and BNO055—were tested under controlled lab conditions. Among them, BNO055 showed the highest accuracy and lowest signal noise. Its onboard fusion algorithm helps differentiate between gravitational and dynamic accelerations.
In Sirobagarh, Uttarakhand, TLS, GNSS, and RTS were deployed for precise surface displacement monitoring. These geodetic tools offered detailed insights into subsidence patterns and slope instability. In Idukki, Kerala, a wireless sensor network was implemented to monitor rainfall, soil moisture, and pore pressure. It supported a three-tier warning system—Early, Intermediate, and Imminent—used effectively in 2009. To overcome power issues in remote areas, DIS-TENG, a self-powered sensor, was introduced. This sensor converts mechanical displacement into electrical signals without external energy sources. Additionally, 5G-integrated sensors (motion detectors, infrared, mobile signal, and GPR) were used for human detection. These systems enabled real-time data transmission for fast rescue and emergency response.
The study underscores the role of smart communication and sensing in landslide risk reduction.
It proposes a robust framework combining diverse sensors and real-time processing tools.
Such integration improves detection precision and enhances early warning capabilities.
The framework ensures timely alerts, faster responses, and greater disaster resilience.
Ultimately, this work aims to safeguard vulnerable regions through proactive landslide management.},
        keywords = {Landslide Monitoring, Sensor Technologies, Early Warning Systems, MEMS IMUs, Wireless Sensor Networks},
        month = {May},
        }