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@article{189305,
        author = {Naik  D C and Bhoomika D and Lokranjan V and Rakesh B T and Rakshitha H L},
        title = {LiDAR-Based Microdrone for Obstacle Detection and Live Streaming System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {7},
        pages = {7719-7725},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=189305},
        abstract = {The use of drones has increased rapidly in recent years due to their ability to perform tasks such as aerial surveillance, inspection, mapping, and monitoring in areas that are difficult or unsafe for humans to access. However, one of the major limitations in drone applications is the risk of collision with nearby objects during flight. This problem becomes more critical in indoor environments, narrow spaces, or locations with multiple physical obstacles. A collision can damage the drone’s hardware, cause loss of control, or result in safety hazards. To overcome this issue, the present project proposes an intelligent obstacle detection and live video streaming system developed using the ESP32-CAM microcontroller and the VL53L0X LiDAR distance sensor. The main objective of this system is to make drone operation safer by alerting the user about possible collisions while simultaneously providing live visual feedback. 
The system is built around the ESP32-CAM, which is a compact and cost-effective microcontroller that supports Wi-Fi connectivity and camera-based video streaming. In this project, the camera module of the ESP32-CAM streams live footage over a Wi-Fi network.},
        keywords = {Drone, Obstacle Detection, ESP32-CAM, LiDAR Distance Sensor, Collision Avoidance System, Real Time Video Streaming, Wi-Fi Connectivity.},
        month = {January},
        }