Smart street lighting
The study's preliminary findings regarding using a single board computer to run an object detection software are presented in the report. These findings are later utilized to create smart street lighting applications. The TensorFlow package is used in Python to produce the object recognition so...
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| Format: | Final Year Project |
| Language: | English |
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Nanyang Technological University
2023
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| Online Access: | https://hdl.handle.net/10356/167624 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | The study's preliminary findings regarding using a single board computer to run an object detection software are presented in the report. These findings are later utilized to create smart street lighting applications. The TensorFlow package is used in Python to produce the object recognition software. The SSDMobileNet V2 artificial neural network model was successfully carried out by the author to construct and test the object detection module on the Raspberry Pi 4B. The findings presented in this research show how this module has the capability for further improvement. The author demonstrated that a decent performance is obtainable with little research funding for the AI module based on simulation and actual findings. This module can accurately estimate the object's distance in addition to having a high-precision object detecting feature. The study additionally suggests a number of ways to improve the created module's performance, particularly its real-time capability. |
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