An Environmental Sensor Network for Air-contamination Monitoring in Subway Stations

초록

Sensor networks incorporate technologies from three different research areas: sensing, communication, and data processing. Within the field of environmental sensor networks, domain knowledge is an essential fourth component. Before designing and installing any system, it is necessary to understand its physical environment and deployment in detail. The system must be able to withstand specific conditions such as temperature, pressure, or vibration. The conventional data flow model in a sensor network is a multiple-source single-sink model. This follows from the typical data querying applications where a remote user collect data from an event observed by several source nodes in a locality or a closed boundary, which may be referred to as the target region. The query is initiated by the sink to the target regions and is flooded within the boundary of the entire target region. Potential for large scale data monitoring through sensor networks has been realized where parameters of interest are compared for extended durations over different geographical locations in space. The installation type of sensor network may be broadly classified by spatio-temporal application including environmental sensing into two classes, infrastructure-based monitoring and field-based monitoring. In the former case, sensor nodes are attached to an existing physical structure to remotely monitor something. The facilities of the infrastructure can be exploited to provide intermittent resource-rich devices that can act as data loggers or data processors or gateway nodes. In the latter case, a given space area is monitored using a dense network of randomly scattered nodes that are not particularly installed on any underlying infrastructure. The purpose is to observe physical phenomena spread over a large region, such as pollution level, presence of chemicals, and temperature levels. In this paper a form of sensor network is operated to monitor air-contamination in subway stations, in combination of infrastructure-based monitoring and field-based one. Observing physical phenomena may produce large amount of environmental data over a wide region, however, we restricted the region scale within the boundary of one station. If the monitoring system incorporates multiple stations, this sensor network may employ distributed databases, and further, possibly with inherent real-time properties in the future. The sensor network is deployed on the two floors, at the platform and the waiting room of a subway station. To reduce the data generation rate and power consumption, the period of sensing and sleeping is set to 30 minutes. Sensor nodes and route nodes are deployed and connected to a sensor network server, SNS, through a micro gateway. Temperature and humidity are sensed under field-based monitoring. These sensors have their own batteries. Dust sensors and CO2 sensors are deployed at particular points and they use external power due to their fast consumptions. Each kind of sensors transmits with Zigbee-based communication.