The combination of photovoltaic cells that can harvest energy from ambient light and artificial intelligence could revolutionize the Internet of Things. Image: Ella Maru Studio.Researchers at Newcastle University in the UK have created environmentally friendly, high-efficiency photovoltaic cells that can harness ambient light to power internet of Things (IoT) devices.
Led by Marina Freitag, the research group from the School of Natural and Environmental Sciences (SNES) has developed dye-sensitized photovoltaic cells based on a copper(II/I) electrolyte. These photovoltaic cells can achieve an unprecedented power conversion efficiency of 38% and a 1.0V open-circuit voltage at 1000 lux (fluorescent lamp). The cells are non-toxic and environmentally friendly, setting a new standard for sustainable energy sources in ambient environments.
This research, reported in a paper in Chemical Science, has the potential to revolutionize the way IoT devices are powered, making them more sustainable and efficient, and opening up new opportunities in industries such as healthcare, manufacturing and smart city development.
"Our research marks an important step towards making IoT devices more sustainable and energy-efficient,” said Freitag, who is a principal investigator at SNES. “By combining innovative photovoltaic cells with intelligent energy-management techniques, we are paving the way for a multitude of new device implementations that will have far-reaching applications in various industries.”
The team also introduced a pioneering energy-management technique that employs long short-term memory (LSTM) artificial neural networks to predict changing deployment environments and adapt the computational load of IoT sensors accordingly. This dynamic energy management system allows the energy-harvesting circuit to operate at optimal efficiency, minimizing power losses or brownouts.
This breakthrough study demonstrates how the synergy of artificial intelligence and ambient light as a power source can help to bring about the next generation of IoT devices. For example, energy-efficient IoT sensors, powered by high-efficiency ambient photovoltaic cells, can dynamically adapt their energy usage based on LSTM predictions, resulting in significant energy savings and reduced network communication requirements.
This story is adapted from material from Newcastle University, with editorial changes made by Materials Today. The views expressed in this article do not necessarily represent those of Elsevier. Link to original source.