# Sensorial Network Framework Embedded in Ubiquitous Mobile Devices
## 1 Introduction
### Problem Definition  
There are several areas that have to be defined at first to understand the core principals of reality in order to properly design the sensorial framework (SF). At first, a considerable amount of information should be collected about the embedded sensors in devices to answer questions about what and how they measure, as well as what their outputs are. Then, the focus should be on real mobile devices, which will be used in experiments. It is also important to concentrate on how these mobile devices interact with users and environments theoretically and practically. Additionally, the key factors, which can influence the framework in certain ways, need to be defined. Finally, the topic of the usability of embedded sensors in cloud-based services needs to be discussed. This attaches an additional value to the present research.  
All sensors consume energy in order to provide their measurements [23; 24]. In the case of mobile devices, it is a challenge to maximize the duration of device usage, without recharging. It was assumed that the energy consumption for localization [25; 26] is the most effective within Global System for Mobile communication (GSM) cell-based evaluation [27]. The energy cost is lower than <20 mW and is followed by WLAN, which has around 500 mJ. On the other hand, the Global Positioning System (GPS) sensor uses the most energy (more than >1000 mJ), depending on the mobile device. Therefore, the sensors used for location estimation have to be considered in relation to the energy efficiency factor. Relative to an accelerometer, a magnetometer has a significantly lower energy consumption, and its sampling of sensors does not pose a significant difficulty in terms of power management. Table 1 shows the measurements of the energy consumption of Samsung S2 smartphone sensors.  
It can be concluded, from those measurements, that the accelerometer is the most efficient sensor for smart phones' motion detection [28]. This means that, when we need to trigger any action, whereby the mobile device starts to move, listening to accelerometer sensorial data is sufficient.  
A suitable solution for the goal of research based on the gathered knowledge can be provided. In this way, it is possible to suggest an effective solution to the battery consumption of mobile devices, available network connectivity, and necessity of provided information. The usage of a sensorial-based cloud service was considered, where sensorial data from a group of users were gathered from mobile devices. These included users' location, activity, or environment, which were recognized by embedded sensors. Figure 3 shows the typical user scenario of a sensorial framework (SF).  
\begin{table}
\begin{tabular}{l c c c} \hline \hline
**Sensor** & **Sampling [MJ]** & **Idle [MJ]** & **Switch ON/OFF [MJ]** \\ \hline accelerometer & 21 & - & -/- \\ \hline gravity & 25 & - & -/- \\ \hline magnetometer & 48 & 20 & -/- \\ \hline gyroscope & 130 & 22 & -/- \\ \hline microphone & 101 & - & 123/36 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Sensor energy consumption of Samsung S2 [27; 28].  
According to the users' behavior, it is possible to create virtual spaces based on similar behavior patterns and share information or artifacts with others. Users can share their recognized location, activities, or environment with others automatically through social connectors or specific applications. Users can automate processes in their surrounding environment by connected elements in the Internet of Things (IoT) [29]. There are many practical uses to which third parties can put this technology. For instance, users can analyze their daily activities. The users' mobile devices connect to a local WiFi spot, recognized as a home environment, and the service can then share such information with relatives or social channels and can start a home welcoming process. The same can be done when a user leaves home to prevent energy loss, lock all entrances, or inform relatives that the user is no longer at home.