Page 28 - ITU Journal, Future and evolving technologies - Volume 1 (2020), Issue 1, Inaugural issue

ITU Journal on Future and Evolving Technologies, Volume 1 (2020), Issue 1

2 transmits, the same phenomenon occurs. Tag 1 now activities in such a fashion is already available in vari-
obtains a sinusoid but with a different fixed parameter. ous other radio technologies, BTTN provides a unique
It turns out that when the respective parameters of the approach due to its entirely batteryless operation, pos-
sinusoids are added, their sum is equal to 4 / , where sibility of ubiquity and hence ability to measure a large
is the distance between the tags and is the wave- number of tag-to-tag channels for very fine grain mea-
length of the excitation signal. From this relationship, surements.
the distance can readily be determined.
5.3 From smart cities to biomedicine
Further, with the same line of reasoning, the tags can
estimate Doppler shifts due to moving tags. Experimen- Since the introduction of the RFID technology in the
tal results suggest that tags can estimate Doppler shifts supply chain area about 15 years ago, the technical lit-
with about the same accuracy as that obtained by active erature has provided numerous articles that promote the
conventional RFID readers. Also, the median tracking concept of smart homes and smart cities. One can eas-
error based on data from two tags can be as low as 2.5 ily imagine a smart home with BTTNs, where the tags
cm [23]. equipped with sensors pepper the space of the home
and where many of them are placed on various types of
5.2 Human interactions objects. The location and tracking of such objects will
then readily be enabled by the functionality described in
An interesting application of BTTNs is related to hu- Section 5.1. Applications in smart cities include use on
man interactions [8]. Here we present a setting where structures like buildings, streets, bridges, and parking
BTTNs serve as a ‘device-free’ activity recognition sys- spaces. The tags (with attached sensors) can be tasked
tem [8]. Namely, when the tags in the network commu- to monitor air pollution, traffic, and availability of park-
nicate with each other, the backscatter channel state is ing spaces. If the tags’ density is high, these operations
influenced by the surrounding environment. The chan- can be completed with high spatial resolution. The BT-
nel state thus carries information that can be used for TNs can also be applied to perform the structural moni-
classification of dynamic activities that take place in the toring of buildings and bridges where abnormalities can
proximity of the tags. As explained earlier, with multi- be detected without actual sensing devices and instead
phase backscattering, the communication between two based on the changes in the backscattered signals due to
tags becomes more reliable. It turns out that this is not the developed abnormalities, (e.g., cracks can be found
the only advantage of the scheme. Multiphase backscat- by detecting changes in distances between two tags be-
tering also helps to quantify channel state information fore and after the appearance of a crack). BTTNs will
that can serve as a unique signature of activities which also find a number of applications in medicine, environ-
in turn allows for their accurate classification. mental sensing, precision farming, and manufacturing.
More specifically, when a Tx tag backscatters the exter- For more details and other applications, see a recent
nal signal with different phases, the Rx tag can compute review on ambient backscatter communication [12].
features of these signals. These features vary accord-
ing to the dynamic alterations of the multipath wire- 6. FUTURE RESEARCH DIREC-
less channel between the tags. When there is no one TIONS
near the communicating tags, the amplitudes of the re-
ceived signals with different phases have features that BTTNs offer a unique system to enable ubiquitous
can serve as no-activity features. Similarly, when a per- massively-deployed IoT. Being batteryless and small
son performs an activity near the tags, the signature of form factor, they can easily blend with everyday ob-
the features takes its own value and carries information jects and thus almost everything can become part of
about the activity. Clearly, it is important to identify the network. Current research has successfully proto-
good features that allow for accurate classification. For typed and evaluated single BBTN links, explored their
example, it has been found that the backscatter chan- ability to characterize the intervening wireless channel
nel phase, the backscatter amplitude, and the change in (RF sensing) with applications to localization, tracking
excitation amplitude between two multiphase probings and activity recognition. Current research has also pro-
have a high discriminatory power for classification [8]. duced theoretical studies on large-scale network routing
issues. But much still needs to be done to make BTTNs
Experimental results suggest that with signals provided practical and their applications realizable. One key issue
by a BTTN, one can recognize human activities with an is effective power harvesting and associated power man-
average error of about 6%. This was accomplished with agement, so that the optimal power is allocated to activ-
8 different activities and 9 individuals. Interestingly, ities such as communication, sensing, and computation
this level of performance is similar to that achieved by at all times. This may limit the computation needed
systems that use powered, active radios. The classifica- for routing and other application level signal processing
tion results were obtained by convolutional neural net- due to a limited power budget. These are trade-offs that
works (for details, see [8]). While the ability to recognize need to be explored in very dense deployments, e.g., tags

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