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Silva, D., Mataloto, B. & Coutinho, C. (2024). COPY Enhancing energy management in IoT networks. In 2024 International Symposium on Sensing and Instrumentation in 5G and IoT Era (ISSI). (pp. 1-6). Lagoa, Portugal: IEEE.

J. Mota et al.,  "COPY Enhancing energy management in IoT networks", in 2024 Int. Symp. on Sensing and Instrumentation in 5G and IoT Era (ISSI), Lagoa, Portugal, IEEE, 2024, pp. 1-6

@inproceedings{mota2024_1742351312169,
	author = "Silva, D. and Mataloto, B. and Coutinho, C.",
	title = "COPY Enhancing energy management in IoT networks",
	booktitle = "2024 International Symposium on Sensing and Instrumentation in 5G and IoT Era (ISSI)",
	year = "2024",
	editor = "",
	volume = "",
	number = "",
	series = "",
	doi = "10.1109/ISSI63632.2024.10720489",
	pages = "1-6",
	publisher = "IEEE",
	address = "Lagoa, Portugal",
	organization = ""
}

TY  - CPAPER
TI  - COPY Enhancing energy management in IoT networks
T2  - 2024 International Symposium on Sensing and Instrumentation in 5G and IoT Era (ISSI)
AU  - Silva, D.
AU  - Mataloto, B.
AU  - Coutinho, C.
PY  - 2024
SP  - 1-6
DO  - 10.1109/ISSI63632.2024.10720489
CY  - Lagoa, Portugal
AB  - This research details the development of a smart lighting system designed to optimize energy consumption by dynamically adjusting the brightness of a Tapo L530E smart lamp based on real-time ambient light measurements. The system integrates a light intensity sensor, an Arduino MKR WAN 1300 Lora, a Sonoff Dual R3 power consumption monitor, and a Tapo L530E smart lamp, with data communication facilitated through The Things Network (TTN) and control logic implemented through Node-RED. The primary goal is to maintain a target light intensity level within a controlled environment, thereby enhancing energy efficiency and user comfort. Preliminary integration and data acquisition have been successfully completed, demonstrating the system’s capability to monitor light levels and power consumption reliably. The ongoing development of a proportional control algorithm aims to adjust the lamp’s brightness dynamically in response to varying ambient light conditions. Initial simulations of the control mechanism indicate promising results, suggesting significant potential for energy savings and consistent lighting conditions. This paper discusses the methodology employed in developing the system, the initial findings, and the anticipated outcomes. The system’s ability to adapt to real-time data is expected to reduce energy wastage and contribute to a more sustainable and efficient lighting solution. Future work will focus on comprehensive testing, detailed data analysis, and exploring the system’s scalability and integration with broader smart home ecosystems. The findings from this research will be presented at the conference, highlighting the potential impact of smart lighting systems on energy conservation and home automation.
ER  -