LIDAR Based Micro-Drone for Birds and Rodents Repellent System
Keywords:
LIDAR, Drone, Proximity sensor, ArduinoAbstract
This project deals with the creation of micro drone that is used as a Birds and Rodent’s repellent system. Rodents are the major vertebrate pests causing damage to various crops and commodities by feeding and indirect damage by spoilage, contamination and hording during on-farm and post-harvest stages. First and foremost, they are disease carriers and cause physical damage to structures. The analysis of the reviews on pre harvest losses indicates a range of 5-15% damage to cereal crops like rice and wheat. During 2001 it was reported that the overall losses of grain to rodents in India were approximately 25% in pre harvest and 25-30% in post-harvest situations bringing the loss to at least US $5 billion annually in stored food and seed grain in India. So, there is a huge need to rid the farm of the rat and mice infestation. In this project, we propose a microdrone with LiDAR technology to provide solution to the agricultural sector. The microdrone low weight, small in size and can be easily launched using our hands and does not produce much noise. By using appropriate way of disturbing the Birds and Rodent’s movements in the field, the harvest losses shall be minimized to a reasonable level.
References
- Kuangyu Zheng, Zimo Ma, Mingyue Zhao: “Joint Efficient UAV Trajectory and Velocity Optimization for IoT Data Collection Using a New Projection Algorithm”, Multidisciplinary Digital Publishing Institute, Vol 6, Issue 12, PP 376, (Nov 2022) https://doi.org/10.3390/drones6120376
- Hao Gu, Jie Yang, Chenhan Hu: “Deep Complex-Valued Convolutional Neural Network for Drone Recognition Based on RF Fingerprinting”, Multidisciplinary Digital Publishing Institute, Vol 6, Issue 12, PP 374, (Nov 2022) https://doi.org/10.3390/drones6120374
- Zixuan Liu, Wei Han, Yu Wu: “Automated Sortie Scheduling Optimization for Fixed-Wing Unmanned Carrier Aircraft and Unmanned Carrier Helicopter Mixed Fleet Based on Offshore Platform”, Multidisciplinary Digital Publishing Institute, Vol 6, Issue 12, PP 375 (Nov 2022) https://doi.org/10.3390/drones6120375
- Jiale Li, Wei Zhou: “LiDAR-Assisted UAV Stereo Vision Detection in Railway Freight Transport Measurement”, Multidisciplinary Digital Publishing Institute, Vol 6, Issue 11, PP 367, (Nov 2022) https://doi.org/10.3390/drones6110367
- Joseph P. Hupy, Cyril O. Wilson: “Modeling Streamflow and Sediment Loads with a Photogrammetrically Derived UAS Digital Terrain Model: Empirical Evaluation from a Fluvial Aggregate Excavation Operation”, Multidisciplinary Digital Publishing Institute, Vol 5, Issue 1, PP 20, (Mar 2021) https://doi.org/10.3390/drones5010020
- Arnold Chi Kedia, Christopher Updike, Amy E. Frazier: “An Integrated Spectral–Structural Workflow for Invasive Vegetation Mapping in an Arid Region Using Drones”, Multidisciplinary Digital Publishing Institute, Vol 5, Issue 1, PP 19, (Feb 2021) https://doi.org/10.3390/drones5010019
- Alberto Sigala, Brent Langhals: Applications of Unmanned Aerial Systems (UAS): A Delphi Study Projecting Future UAS Missions and Relevant Challenges, Vol 4, Issue 1, PP 8, (Mar 2020) https://doi.org/10.3390/drones4010008
- Faiyaz Ahmed, J. C. Mohanta, Pankaj Singh Yadav: “Recent Advances in Unmanned Aerial Vehicles: A Review”, Multidisciplinary Digital Publishing Institute, Springer Link, Vol 5, Issue 47, PP 7963 - 7984 (Apr 2022) https://link.springer.com/article/10.1007/s13369-022-06738-0
- Taleatha Pell, Joan Y. Q. Li, Karen E. Joyce: “Demystifying the Differences between Structure-from-MotionSoftware Packages for Pre-Processing Drone Data” Multidisciplinary Digital Publishing Institute, Vol 6, Issue 1, PP 24, (Jan 2022) https://doi.org/10.3390/drones6010024
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