<p dir="ltr">Due to the rapidly evolving landscape of the Internet of Things (IoT), efficient<br>communication solutions are increasingly sought after. The thesis delves into<br>the development and validation of two optical communication systems (IDC,<br>2021). Capitalizing on the benefits of Optical Wireless Communication (OWC)<br>and Optical Frequency Identification(OFID), two innovative optical systems are<br>introduced: a single-pixel OFID optical reader and a computer vision-based<br>communication system that utilizes an OLED tag, a camera, and a laptop as a<br>reader. These systems are designed to surpass the challenges associated with<br>existing technologies like RFID and Bluetooth, offering enhancements in<br>security, privacy, and autonomy through the integration of energy harvesting<br>technologies. Moreover, the practical application of these systems in real-world<br>settings, such as animal and object identification, highlight their versatility<br>and potential for diverse IoT applications. The prototypes presented were<br>systematically developed and subjected to a series of evaluations to assess their<br>performance. These tests focused on measuring the communication distance<br>achieved, the power consumption of the devices, and the accuracy of data<br>transmission. The experiments demonstrated the technical feasibility of the<br>systems in real IoT environments, affirming their effectiveness in overcoming<br>distance limitations and energy efficiency challenges and providing an<br>alternative solution for accurate data transmission in environments where radio<br>communications cannot operate. These findings underscore the significance and<br>applicability of optical communications.<br>highlight<br></p>
Identifer | oai:union.ndltd.org:purdue.edu/oai:figshare.com:article/24760134 |
Date | 12 December 2023 |
Creators | Diana Alejandra Narvaez (17593545) |
Source Sets | Purdue University |
Detected Language | English |
Type | Text, Thesis |
Rights | CC BY 4.0 |
Relation | https://figshare.com/articles/thesis/IoT_Wireless_Communication_Based_on_Optical_Frequency_Identification_for_Object_Detection_and_Tracking/24760134 |
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