users. Adaptive low-power design [22] proposes a multi-layer hierarchy architecture for BSN thus dividing the BSN into the following layers: A system layer which is a PC or server in hospitals managing the control path and the data path for the BSN by sending commands to the application layer and receiving data. Determining the lowest energy data path is the most important function of this layer. An application layer controlling all the sensor groups by sending commands and receiving data from them. A sensor group layer that includes several sensor nodes. The body area is divided to several sub-areas and each sensor group consists of sensors in one area. A sensor that includes only one sensor node receiving commands from a sensor group and sending the detected data to the sensor group. Hierarchy architecture helps the spread of the BSN to a greater number of sensor nodes with the least changes in higher levels. When both the data source (e.g., BSN) and the destination (e.g., caregiver or physician) are two mobile nodes, an open source framework named SenseFace application [15] is proposed to connect them to each other. The destination is a social network such as fax, email, voicemail, short message (SMS), file attachment, Facebook, YouTube, LinkedIn, tweeter, etc Energy Conservation Energy can be remotely fed to the sensor nodes. Adaptive threshold rectifier (ATR) [9] is a remote method to deliver the energy to several small nodes such as electrocardiograph (ECG). This rectifier wirelessly feeds the sensor node by an adhesive bandage. Energy is delivered remotely by ATR with 54.9% efficiency. This method is not expandable for all nodes due to an extra bandage over each sensor and almost twice as much in extra power expanded. Other energy conservation methods are proposed on PHY and MAC layer. Energy Saving and Harvesting in PHY Application-specific integrated circuit (ASIC) defines three different modes [20]. The first mode is the mode in which nodes communicate with each other through the “active”
users. Adaptive low-power design [22] proposes a multi-layer hierarchy architecture for BSN thus dividing the BSN into the following layers: A system layer which is a PC or server in hospitals managing the control path and the data path for the BSN by sending commands to the application layer and receiving data. Determining the lowest energy data path is the most important function of this layer. An application layer controlling all the sensor groups by sending commands and receiving data from them. A sensor group layer that includes several sensor nodes. The body area is divided to several sub-areas and each sensor group consists of sensors in one area. A sensor that includes only one sensor node receiving commands from a sensor group and sending the detected data to the sensor group. Hierarchy architecture helps the spread of the BSN to a greater number of sensor nodes with the least changes in higher levels. When both the data source (e.g., BSN) and the destination (e.g., caregiver or physician) are two mobile nodes, an open source framework named SenseFace application [15] is proposed to connect them to each other. The destination is a social network such as fax, email, voicemail, short message (SMS), file attachment, Facebook, YouTube, LinkedIn, tweeter, etc Energy Conservation Energy can be remotely fed to the sensor nodes. Adaptive threshold rectifier (ATR) [9] is a remote method to deliver the energy to several small nodes such as electrocardiograph (ECG). This rectifier wirelessly feeds the sensor node by an adhesive bandage. Energy is delivered remotely by ATR with 54.9% efficiency. This method is not expandable for all nodes due to an extra bandage over each sensor and almost twice as much in extra power expanded. Other energy conservation methods are proposed on PHY and MAC layer. Energy Saving and Harvesting in PHY Application-specific integrated circuit (ASIC) defines three different modes [20]. The first mode is the “active” mode in which nodes communicate with each other through the
Msc%20Seyed%20Mahdi%20Shahrokhi%202013.docx