1 research outputs found

    Automated building monitoring using a wireless sensor network

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    Building monitoring is one of the challenging issues in building construction, due to its high cost and the time consuming procedure for implementation and maintenance. It is also a critical issue that directly affects building security, safety, and management, energy saving, and tenants' convenience. Wireless sensor networking is a new networking technology that holds great promise for monitoring, evaluation and management of buildings. However, sufficient work has not been done in the application part of wireless sensor networks for building monitoring. In this thesis, we show how advanced wireless sensor technology can be used by building managers to monitor climate conditions, brightness level, lamp status and room occupancy in buildings as well as by the wireless sensor network administrator to monitor the nodes' connectivity and conditions in the network. We conceive of the building monitoring application as being divided into three main parts. First, wireless sensor hardware is programmed to process signals from sensors and transmit the data in a suitable format to a gateway/server application using multi-hop routing. The second task involves the forwarding of the signals sent by the wireless sensor nodes to the end user application by the gateway/server further retrieval and analysis. The third part consists of an end user application for processing the sensor data sent by the wireless sensor nodes and then forwarded by the gateway/server. The end user application visualizes the network topology, network connectivity graph and real time information of individual motes. In addition, this application provides the real time analysis of the data and functionalities for search and observation. Finally, the end user application allows users to analyze the rooms and network conditions by mining the database using different parameters such as the type of data and the time of data acquisition. The system and related analysis were applied on a real case study -- the eighth and ninth floors of the Engineering and Visual Arts building of Concordia University
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