**4. Sensing**

Internet of Things (IoT) architectures provide means to interconnect people, devices, and to deal with different wireless networks, which regarding its interoperability facilitate the use of smart applications [36]. The progress of mobile wireless communication has allowed to improve sensing systems. One might say that those sensing systems has been continuously adjusted to concepts of speed, technology, frequency, data capacity, framework. A promised field are future generation 6G/7G wireless network regarding its advanced characteristics, expectations. The sixthgeneration wireless network enables sensing solutions with "fine range, Doppler and angular resolutions, as well as localizations to cm-level degree of accuracy" [37]. 7G is identical to 6G regarding global coverage, additionally defining satellite functions for mobile communications [38]. On one hand, "new materials, device types, reconfigurable surfaces will allow the network operations to reshape and control the electromagnetic response of the environment". On the other hand, according to the same source, machine learning, and artificial intelligence will allow us to address the major challenges in communication systems. 6G might simultaneously provide ubiquitous communication and provide high accuracy localization and high resolution sensing services. Hight frequency bands allow fine resolution in different dimensions (range, angle, doppler). It allows both active and passive sensing. The former, active sensors emit the sounding waveforms and process echoes concerning the image doppler and angle information. While the latter, transmit natural reflection of surfaces and arrays of pictures, that represents the image. Sensing applications may exploit a vast wider channel with a bandwidth above 100 GHz [39].

Future networks, allows the combination of several materials and technologies in order to create smart innovative contexts. Intelligent Reflective Surface (IRS) [40] technology encloses an array of units, that occur modifications in the incident signal [41]. Those changes may occur in terms of phase, amplitude, frequency, or polarization. In a broad sense, IRS configures the wireless environment to facilitate transmissions between sender and the receiver [42].

Beam scanning technology, it is possible to generate images of the physical spaces, implementing systematic monitoring of the received signals using steering algorithms. Thus, we can create conditions for future "wireless reality sensing" in the university context [43]. Additionally, might be used miniaturized radars for gesture detection, smartphones, monitoring systems with bio-signals. Sensing and location might guide communication sharing mapping information between devices [37].

To date there is a scarcity of studies focused on attention, emersed on those smart environments. Would be important to add new knowledge, studying attention in innovative smart environments created with aforementioned technologies. Specifically, including precision sensing devices and considering the future wireless network generation applied to the study of attention in e-learning. There are promising devices, that regarding their characteristics might be used to study student

attention. Traditional devices identified in **Table 1** entitled "Sensory-based mechanisms for detection of user's attention in e-Learning" function as a basis to identify new devices to student attention. Thus, analogous devices might be used in new wireless network generation scenarios. For instance: biosensors, webcam, electroencephalogram, Augmented Reality / Virtual Reality glasses that have recently been used to study attention. Biosensors, highly compact and wearables, have the potential to be used to provide continuous real-time physiological information through contactless measurements. One of the main advantages of such devices is the permeability to adapt to a variety of technological contexts, and its usage within the expansion of wireless communication networks. Next it is described one of such scenarios.
