Energy and AoI-aware Data Transmission in Internet of Body (IoB)

The Internet of Bodies (IoB) is a network comprising wearable, implantable, injectable, and ingestible low-powered intelligent sensors placed on, in, and around the human body. These sensors are responsible for collecting the emergency health status of critical patients located in remote areas or hospitals. The data collected by these sensors needs to be transmitted to the monitoring center (i.e., the cloud) as quickly as possible to avoid critical situations. Since these sensors have low-power batteries and limited computational capacity, they require multi-hop transmissions within both intra IoB and inter IoB networks. Inter IoB networks involve information forwarding between bodies and local access points. Furthermore, due to the dynamic movement of the human body and place of the sensor in/on human body, channel state information changes dynamically within both intra and inter IoB networks. To extend the lifetime of IoB sensors and minimize the age of information, cross-layer optimization is needed for bandwidth allocation, transmit power allocation, and next-hop selection in both intra IoB and inter IoB networks. Therefore, the goal of this project is to design low-complexity data driven adaptive machine learning algorithms that leverage cross-layer design to minimize energy consumption and Age of Information (AoI) in IoB to support the Internet of Medical Things.