Associate Prof. Shereen Aly Taie, Associate Professor in the Department of Artificial Intelligence, Faculty of Management, Professional Technology and Computers at the Egyptian Russian University, and A Head of the Artificial Intelligence Research Group at the Faculty of Computers and Information, Fayoum University, participated in cooperation with researchers from the Electronic Research Institution, Faculty of Engineering Cairo University, and “Zewail City of Science and Technology,” in creating an artificial intelligent system that relies on the Internet of Things to control the museum’s Ambience and preserve of its contents of artifacts.

This research develops an Internet of Things (IoT)-based system for museum monitoring and control. The developed system does not only autonomously set the museum ambience to levels that preserve the health of the artifacts and provide alarms upon intended or unintended vandalization attempts, but also allows for remote ambience control through authorized Internet-enabled devices. A key differentiating aspect of the proposed system is the use of always-on and power-hungry sensors for comprehensive and precise museum monitoring, while being powered by harvesting the Radio Frequency (RF) energy freely available within the museum. This contrasts with technologies proposed in the literature, which use RF energy harvesting to power simple IoT sensing devices. We use rectenna arrays that collect RF energy and convert it to electric power to prolong the lifetime of the sensor nodes. Another important feature of the proposed system is the use of deep learning to find daily trends in the collected environment data. Accordingly, the museum ambience is further optimized, and the system becomes more resilient to faults in the sensed data.

The results of this research were published, in a research paper entitled “RF Energy Harvesting IoT System for Museum Ambience Control with Deep Learning” in the international journal “MDPI SENSOR”. It is noteworthy that the magazine “MDPI SENSOR” ranks (76) out of a total of (12515) journals in the field of computer science, and it is included in the “Web of Science” classification with an Impact Factor of (3.275), as well as within the international classification of “Scopus”.