University of Twente Student Theses
Increasing the accuracy of rodent detection and estimation of the population with sensor fusion
Dadhich, S. (2022) Increasing the accuracy of rodent detection and estimation of the population with sensor fusion.
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| Abstract: | A wide number of rodents pose significant threats to agriculture, human health, and infrastructure. This paper, present a novel method for detecting and capturing rodents using a combination of sensor technologies. The detection and estimation of the rodent population are achieved using Radar sensors, while a Raspberry Pi camera and Ultrasonic microphone are employed to capture images and recordings of rodents inside the trap. PIR sensors are used to activate the radar, camera, and microphone when the presence of rodents is detected. To further classify the rodents, YOLOV4 and PointNet algorithms are used for object detection and point cloud classification, respectively. This method of trapping rodents is humane, and the classification of rodents enables the capture of certain useful species that can be reintroduced into ecosystems to perform vital roles in seed dispersal, soil aeration, and food chains. The findings of this research demonstrate the effectiveness of the proposed method by combining the sensor technology in detecting and capturing rodents while facilitating their classification for further research and conservation efforts. |
| Item Type: | Essay (Master) |
| Faculty: | EEMCS: Electrical Engineering, Mathematics and Computer Science |
| Subject: | 53 electrotechnology, 54 computer science |
| Programme: | Embedded Systems MSc (60331) |
| Link to this item: | https://purl.utwente.nl/essays/94837 |
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