1st International Workshop on Mobile Sensing with Radio, Light, and Acoustic

Session MSRLA


1:00 PM — 3:20 PM JST
Dec 16 Wed, 11:00 PM — 1:20 AM EST

A Privacy-preserving and Collusion-resisting Top-k Query Processing in WSNs

Jianguo Zhou, Hua Dai, Jie Zhu, Rongqi Qi, Geng Yang, Jian Xu (Nanjing University of Post and Telecommunication, China)

In the wireless sensor networks, it is a challenging
issue to protect the data privacy from curious users while
providing top-k query services. In this paper, a novel privacypreserving
and collusion-resisting top-k query processing interactive
protocol is proposed for WSNs. To the best of
our knowledge, it is the first work providing the privacy
preservation and collusion resistance simultaneously in topk
query processing in WSNs. Data encryption with different
private keys, the bloom filter and HMAC are adopted to achieve
data privacy preservation even there are a few sensors colluding
with the adversaries. During the interactive procedures of the
query processing, two rounds of secure interactions between
the sink and sensors are performed to obtain the query results.
The protocol analysis indicates that the protocol can preserve
data privacy even a few sensors collude with the adversaries,
while the experiment result shows that the proposed protocol
has good performance on network communication cost.

AcousticThermo: Temperature Monitoring using Acoustic Pulse Signal

Fusang Zhang (Institute of Software, Chinese Academy of Sciences, China); Kai Niu (Peking University, China); Xiaolai Fu (Beijing University of Posts and Telecommunications, China); Beihong Jin (Institute of Software, Chinese Academy of Sciences, China)

Temperature is an important indicator for agriculture
irrigation, industrial manufacture, food safety, etc. While
temperature measurement can be achieved via dedicated sensors,
there still have a demand to sense temperature with ubiquitous
computing devices. In this paper, we propose to enable the
sound signal to measure the air temperature using commodity
acoustic devices. Different from existing FMCW and OFDM
based acoustic sensing system, we are the first to employ acoustic
pulse signal and get rid of offsets to obtain the accurate sound
speed. Then we precisely obtain temperature by quantifying
the relation between sound speed and temperature. We build a
temperature monitoring prototype named AcousticThermo, and
conduct extensive experiments. Experimental results show that
the proposed system can achieve an average estimation error of
below 0.2?C in various temperature environments.

A Collision-free MAC protocol based on quorum system for underwater acoustic sensor networks

Guangjie Han, Xingjie Wang, Ning Sun, Li Liu (Hohai University, China)

The research of underwater acoustic sensor networks (UASNs) has gained much attention because of its wide applications, such as environmental monitoring and seabed oil exploration, etc. However, underwater acoustic communication has certain specific characteristics, such as low transmission rate, high delay, and limited energy, which have challenged the data transmission of UASNs. This paper is dedicated to solving the problem of transmission collisions between sensor nodes at the MAC layer in UASNs. A Collision-free MAC protocol for UASNs is proposed, which is a global TDMA-based MAC protocol and optimizes the quorum system based on the network topology to reduce unnecessary time slot allocation and improve the channel utilization. Compared with previous MAC protocol, the result of simulation has shown the superior performance of the proposed MAC protocol both in terms of reducing latency and saving energy consumption.

Gesture Recognition System Based on Neural Networks by Using COTS RFID Tag Array

Jiaying Wu, Chuyu Wang, Lei Xie (Nanjing University, China)

Nowadays, gesture recognition plays a more and
more important role in human-computer interaction. In this
regard, contact sensors or computer vision have made some
progress, but they also have shortcomings in portability or privacy.
In this work, we propose a gesture recognition system which
uses RFID tag array and neural networks to recognize gestures.
By using an RFID tag array, we can obtain gesture information
in a non-contact, non-infringing manner. By combining CNN
and LSTM as CNN-LSTM, we can focus on both spatial and
temporal features and get better performance. Experiments show
that the accuracy of the system on the test set is 92.17%, and it
performs well in recognizing different gestures of different users
at different speeds.

Real-time and Accurate RFID Tag Localization based on Multiple Feature Fusion

Shupo Fu, Shigeng Zhang, Danming Jiang (Central South University, China); Xuan Liu (Hunan University, China)

We propose a new radio frequency identification
(RFID) localization approach that achieves both low latency and
high accuracy by fusing multiple type of signal features. Existing
RFID tag localization approaches either suffer from large localization
latency (e.g., approaches based on phase measurements),
or cannot provide high localization accuracy (e.g., approaches
based on received signal strength (RSS)). We propose a two-step
approach that fuses phase measurements and RSS measurements
to resolve this dilemma. First, coarse-grained RSS measurements
are utilized to figure out a small bounding box that encloses the
position of the target tag. Second, fine-grained phase measurements
are used to refine the position estimation of the target tag in
the bounding box. Experimental results show that the proposed
fusion approach achieves centimeter-level localization accuracy
with less than 10 feature measurements, reducing localization
latency by more than one order of magnitude when compared
to state-of-the-art solutions.

Research and Development of a portable device for measuring the concentration of colloidal solution

Cunbo Jiang, Chenguang Sun, Zhe Lan, Hongxiang Xiao, Jinfang Nie (Guilin University of Technology, China)

It is necessary to measure the concentration of
colloidal solution in field water survey and research. In some
cases, the colloidal solution will be denatured quickly after
leaving the mother liquor. Therefore, it is necessary to
sample and measure its concentration on the spot. A
portable automatic measuring instrument for the
concentration of colloidal solutions can solve such problems.
It is equipped with a measurement software system and its
own measurement environment to meet the working
environment of image sensors and concentration
measurement; it uses a light source driver to provide a highstability
drive current for the semiconductor laser light
source to achieve constant current and constant power
control; uses a stepper motor to complete the measurement
Free and stable switching between workstations; finally
combined with digital image analysis to achieve
concentration measurement. Research and experimental
results show that the device runs stably and improves the
timeliness of concentration measurement, and the
measurement error is controlled within the expected range.
The instrument is small in size, low in power consumption,
and subject to environmental constraints to meet the needs
of on-site sampling and testing.

Spectrum Prediction Based On Joint Long And Short Term Memory With Convolutional Neural Network In Cognitive Sensing For Spectrum Sharing

Liang Zhang, Min Jia, Qiyu Huang (Harbin Institute of Technology, China); Yun Liu (The 54th Research Institute of China Electronics Technology Group Corporation, China)

In cognitive radio context, spectrum sensing is
the vital technique for the cognitive users to acquire the
spectrum of frequency band. It requires cognitive users to
determine the usage state of the spectrum through
spectrum perception and access the spectrum for
communication when the spectrum is idle. However, the
accuracy of single radio spectrum is low. Thus, the
proposed algorithm adopts the joint CNN and LSTM
prediction model carries out combined design to obtain the
prediction model, which is used for spectrum prediction
under multi-channel. The simulation results show that and
the sensing accuracy of radio spectrum is significantly

Session Chair

Jia Liu (Nanjing University, China)

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