Sensors 2009, 9, 8824-8830; doi:10.

3390/s91108824
OPEN ACCESS

sensors
ISSN 1424-8220
www.mdpi.com/journal/sensors
Editorial

Wireless Sensor Technologies and Applications

Feng Xia

School of Software, Dalian University of Technology, Dalian 116620, China; E-Mail: f.xia@ieee.org

Received: 20 October 2009; in revised form: 31 October 2009 / Accepted: 2 November 2009 /
Published: 4 November 2009

Recent years have witnessed tremendous advances in the design and applications of wirelessly
networked and embedded sensors. Wireless sensor nodes are typically low-cost, low-power, small
devices equipped with limited sensing, data processing and wireless communication capabilities, as
well as power supplies. They leverage the concept of wireless sensor networks (WSNs), in which a
large (possibly huge) number of collaborative sensor nodes could be deployed. As an outcome of the
convergence of micro-electro-mechanical systems (MEMS) technology, wireless communications, and
digital electronics, WSNs represent a significant improvement over traditional sensors. In fact, the
rapid evolution of WSN technology has accelerated the development and deployment of various novel
types of wireless sensors, e.g., multimedia sensors. Fulfilling Moores law, wireless sensors are
becoming smaller and cheaper, and at the same time more powerful and ubiquitous.

Figure 1. Wireless sensor architecture.

Sensing Unit Processing Unit Communication

Unit (Transceiver)
Sensor1 ADC Microcontroller
...... Transmitter
SensorN ADC Storage
Receiver

Power Supply

As shown in Figure 1, there are typically four main components in a sensor node [1], i.e., a sensing
unit, a processing unit, a communication unit, and power supply. The sensing unit may be composed of
one or more sensors and Analog-to-Digital Converters (ADCs). Sensors are hardware devices that
measure some physical data of the monitored systems state such as temperature, humidity, pressure,
or speed. The analog signals produced by the sensors are digitized by ADCs and sent to the processing
Sensors 2009, 9 8825

unit for further processing. Within the processing unit, there is a microcontroller associated with a
small storage unit including on-chip memory and flash memory. The processing unit is responsible for
performing tasks, processing data, and controlling the functionality of other components of the sensor
node. A wireless sensor connects with other nodes via the communication unit, where a transceiver
encompasses the functionality of both transmitter and receiver. The wireless transmission media may
be radio frequency, optical (laser), or infrared. At present, the main type of power supply for wireless
sensor node are sbatteries, either rechargeable or non-rechargeable. Energy is consumed for sensing,
data processing, and communication. For small wireless sensor nodes (with limited computing
capacity), data communication will expend the majority of energy, while sensing and data processing
are much less energy-consuming.
In the past one and a half decades, a number of prototype and commercial wireless sensor nodes
have been made available by research institutions and companies from around the world. Although
these sensor nodes often differ in capacity and feature, most (if not all) of them have been built upon
the architecture given in Figure 1. Table 1 gives a list of some available wireless sensor nodes.

Table 1. Some available wireless sensor nodes.

Node Sensing Unit Microcontroller Memory Transceiver

BTnode UART, SPI, I2C, GPIO, ATmega 128L 4KB EEPROM, Chipcon CC1000;
ADC, etc 64KB SRAM, Zeevo ZV4002
128KB FLASH Bluetooth
FireFly Sensor expansion card: ATmega 1281 8KB RAM, Chipcon CC2420
temperature, light, 128KB ROM
acoustic, etc
IMote2 UART, SPI, I2C, SDIO, Intel PXA271 256KB SRAM, CC2420
GPIO, etc 32MB FLASH,
32MB SDRAM
MicaZ Expansion connector ATmega 128L 4KB RAM, CC2420
for light, pressure, 128KB FLASH
acceleration, etc
SunSPOT Temperature, light, ARM 920T 512KB RAM, CC2420
acceleration, etc 4MB FLASH
TinyNode584 On-board temperature TI MSP430 10KB SRAM, Xemics XE1205
sensor 48KB FLASH
Tmote Sky On-board humidity, TI MSP430 10KB RAM, CC2420
temperature and light 48KB FLASH
sensors

The proliferation of these products opens up unprecedented opportunities for a wide variety of
scientific, industrial, agricultural, commercial and military applications, such as health care, smart
transportation, emergency response, home automation, social studies, critical infrastructure protection,
and target tracking, just to mention a few. In particular, wireless sensor and actuator networks are a
key enabling technology for cyber-physical systems [2,3], which will ultimately improve the quality of
Sensors 2009, 9 8826

our lives. To realize the full potential of wireless sensors, enormous challenges need to be addressed
and significant efforts have been made in this field.

In This Issue

The objective of this Special Issue was to gather the latest research and development achievements
in the field of wireless sensors and to promote their real world applications. Special attention is paid to
several important aspects of wireless sensor technologies, i.e., sensor networking, localization, and
power management, as well as design, implementation, and applications of wireless sensors. The issue
includes a total of 46 high-quality papers, which are expected to give the readers some insight into the
current state of the art
A considerable portion of these papers deal with diverse issues in sensor networking. Qiu et al. [4]
introduce a unified multi-functional dynamic spectrum access framework. Jung and Park [5] propose a
cache-based sensor network bridge, which enables sensing data reusability and customized WSN
services. Hung et al. [6] present an energy-efficient secure routing and key management scheme for
mobile sinks in sensor networks. Availability and end-to-end reliability in low duty cycle multi-hop
WSNs are addressed by Suhonen et al. in [7]. A MAC-aware data aggregation method is proposed
in [8] by Li and co-workers to minimize the total energy consumption of data transmission.
Qiu et al. [9] propose the priority-based coverage-aware congestion control algorithm which is
distributed, priority-distinct, and fair. Amin et al. [10] design a robust intrusion detection system for
IP-based sensor networks. Son et al. [11] study the problem of how to alleviate the exposed terminal
effect in multihop wireless networks in the presence of log-normal shadowing channels. Other topics
examined include distributed joint source-channel coding [12], network coverage [13,14], sensor
deployment [15,16], fault detection [17], and security [18-20]. Some important aspects of WSNs are
reviewed in [21] and [22].
The knowledge of position is indispensable for many applications and services provided by WSNs.
Teng et al. [23] introduce a range-free, distributed and probabilistic mobile beacon-assisted
localization approach for static WSNs. They also present an improved version of the approach.
Pei et al. [24] propose an anchor-free localization method for mobile targets based on non-metric
multi-dimensional scaling and rank sequence. A network-based mobility scheme for mobile
6LoWPAN nodes is presented by Bag et al [25]. Lloret et al. [26] propose a hybrid stochastic
approach to self-location of wireless sensors in indoor environments. Jeon et al. [27] propose a sink-
oriented dynamic location service for handling sink mobility.
Saving energy is of paramount importance for wireless sensors. Knight et al. [28] review the state-
of-the art technology in the field of both energy storage and energy harvesting for sensor nodes.
Priya et al. [29] review the progress made in the synthesis of thick film-based piezoelectric and
magnetoelectric structures for harvesting energy from mechanical vibrations and magnetic field. The
problem of sensor scheduling with a mobile sink is studied by Maheswararajah et al. [30], with focus
on minimizing the total energy consumed by sensor nodes while avoiding measurement losses. Two
sleep scheduling management schemes for WSNs are presented in [31]. In [32], high-resolution images
with a wide field of view are generated with minimum energy dissipation. An adjacency matrix-based
transmit power control method is presented by Consolini et al. in [33].
Sensors 2009, 9 8827

Several papers are about the design of application-oriented sensors. In [34] Wang et al. develop a
passive wireless temperature sensor, capable of working in harsh environments and suitable for
monitoring high temperature rotating components. A wireless sensor node for precision horticulture
which permits the use of precision agricultural instruments based on the SDI-12 standard is developed
in [35]. Rodrigues et al. [36] present the design and implementation of an intra-body sensor for
acquisition and monitoring of intra-vaginal temperatures. Bartolozzi and Indiveri [37] present a
neuromorphic VLSI device, i.e., the Selective Attention Chip, which can be used in multi-chip
address-event systems.
Sensor-based applications have been reported in a number of papers. Jurdak et al. [38] propose to
integrate sensor networks with medium range wireless mesh networks to realize large scale
environmental monitoring. Song et al. [39] develop a mobile sensor network system for monitoring
applications in unfriendly environments. Key technologies for wireless monitoring of intelligent
automobile tires are discussed in [40]. Wang and Niu [41] propose a method for spatial forecast of
landslides in Three Gorges using the spatial data mining technology. Raza et al. [42] present a web
portal framework for sensor-based applications in pervasive computing environments. Zhang et al. [43]
introduce a two-stage approach to the detection of people eating and/or drinking for the purpose of
living surveillance. The design and evaluation of a WSN based aircraft strength testing system is
reported in [44]. Water monitoring using wireless sensors is reported in [45]. Handcock et al. [46]
realize the monitoring of animal behaviour and environmental interactions using ground-based sensors,
GPS collars and satellite remote sensing. The relevance of using open hardware and software motes for
environment monitoring is assessed by Bagula et al [47]. Antoine-Santoni et al. [48] deal with a WSN
as a reliable solution for capturing the kinematics of a fire front spreading over a fuel bed. Wireless
sensor technologies and applications in agriculture and food industry are reviewed in [49].
It is my hope that the readers would find this Special Issue interesting and useful in their research
and development work. I would like to express my whole-hearted thanks to all the authors who have
submitted their papers to this issue. I am also very grateful to all the reviewers for their valuable
comments and suggestions that guarantee the quality of the papers published. Finally, I want to thank
Dr. Ophelia Han, Mr. Dietrich Rordorf, Mr. Matthias Burkhalter, Dr. Shu-Kun Lin and their staff at
the Sensors Editorial Office for their great support and the opportunity to run this Special Issue.

Acknowledgements

The work of the author is partially supported by Natural Science Foundation of China under Grant
No. 60903153.

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