Risk Monitoring of Buildings Using Wireless Sensor Network

Risk Monitoring of Buildings Using Wireless Sensor Network N. Kurata Planning Section, Kobori Research Complex, Kajima Corporation, Minato-ku, Tokyo, 107-8502, Japan B.F. Spencer, Jr. Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA M. Ruiz-Sandoval Department of Civil and Geological Sciences, University of Notre Dame, Notre Dame, IN, 46556, USA

ABSTRACT: A risk monitoring of buildings for natural and man-made hazards mitigation is discussed in this paper. Ubiquitous monitoring using a network of wireless sensors is one of the most promising emerging technologies for this purpose. A smart sensor based on the “Berkeley Mote” platform was introduced, and application to the next generation of structural health monitoring and control was recently proposed (Spencer et al., 2002, Spencer 2003). Herein, the performance of the “MICA Mote” is investigated through free vibration and shaking table tests of a two story steel structure. The MICA Mote as a wireless acceleration sensor is shown to have sufficient performance for the intended purpose. 1 INTRODUCTION

A number of studies have been conducted on structural health monitoring for buildings and civil engineering structures in recent years (Spencer et al. 2002, Spencer 2003, Dyke et al. 2000, Fujino & Abe 2002, Iwan 2002, Mita & Takahira 2002). Some of these studies have focused on wireless sensing technology. Researchers at the Stanford University have developed a wireless sensing unit for real-time structural response measurements and conducted a series of validation tests (Lynch et al. 2002, Lynch 2002). The Mitsubishi Electric Corporation has developed energy-saving wireless sensor network and also the University of Tokyo and the Oki Electric Industry have devoted their effort to develop new wireless sensor networks (Skyley networks 2003). A commercially available wireless sensor platform called the “Berkeley Mote” with an operating system was provided by researchers at the University of California, Berkeley (Horton et al. 2002, Wait et al. 2002), and its application to the next generation of structural health monitoring and control was recently proposed (Spencer et al. 2002, Spencer 2003). Because of its open hardware and software platform, the Berkeley Mote has a possibility as a useful tool for research activities. In this paper, the feasibility of monitoring of various risks for buildings by using the smart sensors is discussed, and the performance of the “MICA Mote” as a wireless acceleration sensor is tested.

“Computing Everywhere” or “Ubiquitous Computing” is expected to be realized over the next ten years. The interest in sensing technology for various uses has been growing, and new kinds of sensors have been developed by micro electro mechanical systems (MEMS) technology. Environmental information, such as brightness, temperature, sound, vibration, and a picture of a certain place in a building, is evaluated by the network to which a huge number of microcomputer chips with sensors were connected (Sakamura 2002). Fig. 1 shows the flow towards a ubiquitous computing/network society. A structural health monitoring technology will play an important role in this stream. 2003 Computer with sensors are getting smaller, smarter and cheaper

2004-2006

2011-2015

Small networks of computer/sensors will be increased.

2007-2010

Ubiquitous Computing/ Network Society

Large scale networks of computer/sensors will appear

Figure 1. Towards a ubiquitous computing/network society.

Kurata, Spencer and Ruiz-Sandoval

1

2 BUILDING RISK MONITORING 2.1 Risk monitoring and hazard mitigation

Wireless sensor network acceleration/strain/ temperature/light/ image/sound/etc.

Buildings are subjected to natural hazards such as severe earthquakes and strong winds, as well as man-made hazards such as fire, crime, and terrorism, during their long-term use. To mitigate these hazards, monitoring various risks in a building by an intelligent sensor network is necessary. The sensor network could measure acceleration, displacement, strain, etc. The risk to buildings includes aging of structural performance, fatigue, damage, gas leak, invasion, fires, etc. According to the results of risk monitoring, appropriate risk control measures such as structural control, maintenance, evacuation guidance, warning, alarm, fire fighting, rescue, security measures, can be applied (see Fig. 2).

Fiber optic network acceleration/strain/etc.

Internet Main server/base station

Figure 3. Example of risk monitoring system. Hazard

Risk Monitoring

Sensor Network

Aging of structural performance/ Fatigue/Damage/Gas leak/ Invasion/Fires/etc.

Acceleration/Displacement/Strain/ Temperature/Light/Image/ Olfactory/Smoke/Sound/etc.

Risk Control

Hazard Mitigation

Structural Control/Maintenance/ Evacuation guidance/Warning/ Alarm/Fire fighting/Rescue/ Security measures/etc.

Natural Hazard (Earthquake, Typhoon, etc.) Man-made Hazard (Fire, Crime, Terrorism, etc.)

Earthquake /Wind

Fire

Crime

Figure 2. Building risk monitoring and hazard mitigation.

3 NETWORK-ENABLED WIRELESS SENSOR MICA MOTE

2.2 Role of sensor networks A wireless sensor network plays an important role in such strategies and can be connected to the internet so that this information can be used for monitoring future risks. Wireless sensors are easy to install, remove, and replace at any location, and are expected to become increasingly smaller (i.e., “smart dust”) by using MEMS technology. They will provide a ubiquitous, networked sensing environment in buildings. For example, acceleration and strain of each beam and column, temperature and light in each room, images and sounds in desired locations can be obtained by the “smart dust” sensors, as illustrated in Figure 3. Additionally, a single kind of sensor such as a condenser microphone can be used for multiple purposes (Yamasaki & Watanabe 2001). Furthermore, a fiber optic network is not only utilized as infrastructure for information technology, but also as a “wired” sensor network. Table 1 shows various kinds of hazards, and possible applications/combination of sensors. Kurata, Spencer and Ruiz-Sandoval

Table 1. Sensor Applications. Application Sensor observation acceleration experiment acceleration, strain structural control acceleration health monitoring acceleration, strain acceleration, strain, damage detection displacement temperature, smoke, fire detection acoustic, acceleration, olfactory gas leak detection olfactory alarm, warning sounder temperature, smoke, evacuation control acoustic, light, olfactory acceleration, acoustic, surveillance light, camera security alert sounder

3.1 Smart dust project This technology is based on the smart dust project supported by the Defense Advanced Research Projects Agency (DARPA) under the Network Embedded Software Technology (NEST) program in the Wireless Embedded Systems at the University of California, Berkeley (Berkeley WEBS). The goal of this project is to explore the fundamental limits to the size of autonomous sensor platforms. Many new applications are expected to become possible when actual “smart dust” can be realized on a millimeter size scale (Pister et al. 1999). 3.2 MICA Mote The MICA Mote (see Photo. 1) has been developed by researchers at the University of California, Berkeley. It is an open hardware and open software platform for smart sensing and consists of plug-in sensor boards, AT-mega 128L processor, 916 MHz 2

3.4 Sensor board

transceiver, and attached AA battery pack as shown in table 2.

A variety of sensor boards for the MICA are available. A MTS310 Sensor Board manufactured by Crossbow Technology, Inc. (2003), which was used in this research, has acceleration, magnetic, light, temperature, and acoustic sensors, as well as a sounder (see Photo. 2). The sensor board can be designed and manufactured freely for each purpose. The “Tadeo sensor board” which is equipped with a high-sensitivity acceleration sensor has developed and tested for the civil engineering applications (Ruiz-Sandoval et al. 2003). Microphone

Photograph 1. Wireless sensor MICA Mote. Table 2. Specifications. Processor/Radio MICA CPU Atmega128 CPU clock 4 MHz Program memory 128 KB Data memory 512 KB AD converter 10 bit 5.5 mA Processor current draw