## 7 Smartphones as Mobile M2M Gateways  
A potential use case for mobile M2M communications is its application in healthcare for remote monitoring of patient vital signs, e.g., activity level, blood pressure, heart rate, temperature, either for ambulatory monitoring of chronic conditions, or for prophylactic reasons, in order to minimize the number of visits to the doctor [11, 26]. In the latter scenario, there are wearable sensors that continuously collect physiologic information and send it to a remote service to be processed and acted upon. Table 3 shows some characteristics of representative traffic originated in current healthcare sensors for remote vital sign monitoring, as presented in [75]. Different physiologic variables have different sampling rates and number of channels. The number of channels reflects the number of different locations of the body from where we are sampling the variables. Although it is not expected that an individual carries an Electroencephalogram (EEG) sensing device the entire day, we can envision the application of such devices in a medical facility, where it might be necessary/useful for continuous remote monitoring. As shown in the table, the EEG is expected to produce a higher data rate than, for example, the body temperature variable. Sensors often forward the collected data to a nearby mobile gateway using short-range wireless technologies, like Bluetooth, for energy saving. This mobile gateway can collect data from only one or several sensors, and forward it to destination service. Instead of simply forwarding information as it arrives, the mobile gateway can collect, aggregate, and eventually process information to reduce the \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Parameter** & **Data Rate (in bps)** & **Sampling Frequency (in Hz)** & **Bits Per Sample** & **Number of Channels** \\ \hline Body Temperature & 2.4 & 0.2 & 12 & 1 \\ Blood Pressure & 1920 & 120 & 16 & 1 \\ Cardiac Output & 640 & 40 & 16 & 1 \\ EEG & 98,304 & 256 & 16 & 24 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Characteristics of representative traffic originated in current healthcare sensors. number of transmissions and eventually the amount of data, and energy consumed in undesired network and protocol overheads. Transmitting the highest possible amount of information in the least number of packets improves resource utilization efficiency. However, different sensor data has different granularity, timeliness requirements, or tolerance to packet loss. For example, EEG data is more important than a room temperature, and, therefore, it will have stricter delivery requirements. Just a single blood pressure sensor with a sampling frequency of 120 Hz, needing 16 bits to send the data, results in 1920 bit per second (Table 3), 6.9 Mbit per hour, and 165 Mbit per day, excluding any communication protocol overheads. The more sensors the mobile gateway has to support, the more data needs to be collected and forwarded. This situation introduces a considerable challenge to the mobile gateways in terms of energy consumption, since they have limited battery life, and can have different time intervals between battery replacement/recharge. Smartphones are an ideal choice to play the role of a mobile M2M gateway in healthcare applications, as they are largely available to the population, are less resource constrained than specialized sensors, and have various connectivity alternatives. Although M2M communications have been thoroughly addressed for healthcare applications [13, 15, 26, 38, 39], most of the literature for healthcare still focus on BANs of sensors, and do not explore scenarios potentiated by the use of smartphones. The use of smartphones for transmission of sensing and monitoring data can lead to undesirable battery depletions, since users use their smartphones mainly for other purposes, mostly personal communication and browsing.