Wireless Sensor Networks: a New Paradigm for Connecting the World

Introduction to Theory and Applications of Self Organizing Wireless Sensor Networks

Vijay Devabhaktuni and James Haslett

RFIC Research Group, ATIPS Lab, Department of Electrical & Computer Engineering, University of Calgary, Calgary, AB, T2N 1N4, Canada

[email protected], [email protected]

Abstract Recent advances in low-cost and low-power wireless communication coupled with progress in ad-hoc networking routing and protocols, have made “wireless sensor networks” a topic of active interest. Typically, hardware components in a wireless sensor network include sensor circuits, analog-to-digital converters, microprocessors, and wireless communications transceivers. These hardware components need to be programmed using software tools to work cooperatively toward accomplishing a user-defined task. The main objectives of such a network are data acquisition and RF transmission. In this paper, we introduce basic concepts in this emerging multidisciplinary research area supported by references to available commercial products. Two classes of wireless sensor network applications in real-life are identified. As part of the on-going work, we have developed a comprehensive design framework of an intelligent wireless patient- monitoring system. This introductory paper is expected to trigger future research projects and strategic collaborations in Canadian microelectronics and wireless arenas.

Keywords - data acquisition, information technology, self organizing, sensors networks, wireless communications

Introduction The recent drive in the information technology industry toward new wireless communication devices and systems and their utilization in addressing a wide variety of real-world problems has resulted in several new areas of active research, wireless sensor networks [1]-[6] being one such hot topic. As we know, the Internet has been able to provide a large number of users with the ability to move diverse forms of information readily and thus revolutionized business, defense, education, industry, research, and science. Sensor networking [7]-[16] may, in the long run, be equally significant by providing measurement of the physical phenomena around us, leading to their understanding and ultimately the utilization of this information for a wide range of practical applications. Potential applications of sensor networking include defense, environmental [7] and habitat monitoring [8], healthcare monitoring [9], transportation [10], manufacturing [11], and search and rescue [12].

Description A typical wireless sensor network consists of a base station and several nodes distributed or positioned in the environment of interest. Each node is expected to detect events of interest and estimate parameters that characterize these events. The resulting information at a node needs to be transmitted to the base station either directly or in “multi-hop” fashion involving automatic routing through several other nodes in the network. Implementation of such a network requires hardware components and corresponding software modules to program these components in a cooperative manner. A commercial hardware platform that we have been investigating consists of processor cum radio boards commonly referred to as “motes”. Each mote, a battery-powered device, consists of a sensor unit, a power unit, a two-way ISM band radio transceiver unit (includes an RF antenna), an ADC unit, a processor that runs TinyOS-based code, and logger memory capable of storing up to 100,000 measurements. A base station consists of a mote attached to a mote-interface-board that is interfaced to a PC via the parallel port. Two types of motes in this commercial system [1], namely, mica2dot and mica2 are shown in Figure 1. Included in the product are sensor boards that directly mate with a mote. These boards consist of sensor modules e.g. accelerometer, magnetometer, microphone, photosensor, thermistor, and in addition, allow integration of user’s own sensors.

(a) (b)

Figure 1. (a) Mica2dot and mica2 motes supplied by Crossbow Technologies Inc. (b) As can be seen, mica2dot is comparable to a loonie in terms of size.

In terms of software, the operating system for programming this particular sensor network is called TINYOS [2]. TinyOS is an event-driven operating system designed for sensor network nodes that have very limited resources (e.g. 8K bytes of program memory, 512 bytes of RAM). The programming language used to control and run the hardware components to perform user- defined tasks is called nesC. nesC is an extension to C designed to embody the structuring concepts and execution model of TinyOS. Software is developed and supported by Berkley.

Reception and transmission is available at different frequencies. Professional mote development kits available in the market allow frequencies of 315MHz, 433 MHz and 868/916 MHz with typical coverage of 1000ft, 1000ft and 500ft respectively. Each mote is powered by an external battery. Power management in wireless sensor networks [13] is an important aspect that will drive research in the next decade, and low-power sensor and RF transceivers are crucial for key applications in this area. The state-of-the-art in power management involves defining “wake” and “sleep” cycles. A mote draws mA current levels in data-gathering or wake mode and only draws μA current levels in sleep mode. Various other practical aspects including feasibility studies [14] [15] are being pursued. Classification of Possible Application Examples As the technology gains popularity, research is becoming important in both theoretical and application domains [3]-[4]. We identify two classes of application examples below.

A. Stationary Network: We define a stationary network as a network of sensor nodes, in which, each sensor node’s position is fixed relative to the base station and other nodes in the network. A demonstrated application in this direction is humidity monitoring in a vinyard [5]. Data acquired by a mote is transmitted to the base station which then processes the information and triggers necessary actions such as localized watering. There are two possible cases to transmit data. When a node is in direct wireless contact i.e. in the range of the base station, direct communication is possible. When a node is not in the range, it transmits data in an ad-hoc environment also referred to as multi-hop. Implementation of an efficient multi-hop system requires optimal routing [16] to facilitate shortest route, reduced power consumption and improved transmission.

B. Network in Motion: An example in this category is a herd of animals on an extensive farm, where each animal is equipped with a sensor node. The animals are in constant motion relative to each other as well as the base station. Such a complicated mobility management requires an even more sophisticated implementation of routing algorithms. In order to maximally benefit from wireless sensor networks of this type, we foresee additional hardware requirements in the form of GPS devices and other forms of mote location.

Application Example in Progress: Wireless Sensor Systems for Patient Monitoring As part of the on-going work, a comprehensive “design framework” of an intelligent wireless patient-monitoring system has been developed. This framework includes real-time sensing of patient’s vital parameters using the motes, and wireless transmission of such critical information over radio frequencies to the base-station. Subsequent data processing on a PC will allow detection of certain medical emergencies, and automatic alerting of medical staff. The overall framework is shown in Figure 2.

In phase I of the project, a simplified prototype system utilizing a basic wireless network kit and sensor components has been implemented for the purpose of experimentation. In phase II of the project, biomedical oriented low-power high-precision sensors will be designed and possibilities of developing a digital (Bluetooth) version of the wireless senor system will be studied for advancement of the prototype. Prototype system will be tested in a hospital environment and will be refined towards meeting ethical, medical and technological standards in phase III. Potential deliverables will include:

 An Ad Hoc self-organizing wireless system capable of close patient-monitoring even when patients are in motion.  A Smart-Bed with increased automation in terms of emergency detection.

These capabilities could lead to efficient use of our valuable healthcare resources.

System Demonstration For the benefit of the wireless conference attendees, we propose to provide a description of system operation, including its relevance to the “TRLabs Home Technologies initiative”. The presentation will include a real-time demonstration of a wireless self organizing sensor network in the conference venue, involving custom sensors developed by the research group. Conclusions A new area of information technology, namely wireless self organizing sensor networks, is introduced. Hardware and software components are briefly described. Application examples are classified into stationary networks and networks in motion. A new application in healthcare sector is proposed and a prototype is implemented for concept demonstration. This area promises networking of the environment surrounding us. An interesting aspect is that this research area brings together various fields of electrical engineering including low power design, RF/wireless communications, signal processing, networking and optimization.

Acknowledgements This work is supported in part by the Natural Sciences and Engineering Research Council of Canada (NSERC), in part by the informatics Circle of Research Excellence (iCORE) of Alberta, and in part by the Telecommunications Research Laboratories (TRLabs). We thank Ken Townsend for his assistance with digital images of motes. We also acknowledge participation of Steven Zhai and Ken Townsend from our research group, and inputs from Andrea Robertson, Lucy Reyes and Sonja Morrison from the Foothills Hospital.

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