Wireless Sensor Networks are based on the ZigBee standard. ZigBee uses the IEEE 802.15.4 physical and MAC (medium access control) layers to provide standards-based reliable wireless data transfer. Also, ZigBee provides low-power wireless connectivity features. The features allow ZigBee-based products to be installed easily and cost-effectively. Thus, this technology has been attracting extensive research and development efforts to replace the traditional wired solutions for Building Automation Systems. However, wireless communications in indoor building environments are prone to be influenced by multiple concurrent factors, such as multi-path fading, channel contention, other radio interference, human activity and limited battery energy. Also, sensor detection is not fully reliable. Thus, system robustness is very concerning in these applications. In this paper, we propose a reliable wireless sensor network and an accurate occupancy detection mechanism. We implemented this system in an indoor building for the lighting control of public areas, including corridors, a coffee room and a washroom. The system framework was shown to be effective in terms of network communication reliability and sensor detection accuracy.

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Wireless sensor networks have the advantages of low cost installation and flexibility, which make them an excellent mechanism for capturing environmental data and interacting with the physical environment for the application of building automation. However, radio propagation suffers from multi-path, shadowing and other radio interference problems in building environments. Therefore, deployment of sensor nodes in a dynamic in-building environment is a complex operation that requires expert knowledge and experience. In this paper, we present a deployment planning tool that can provide a set of useful tools for deploying a wireless sensor network in the building environment. The proposed deployment planning tool provides design tools that can assist users to develop a network infrastructure in order to support reliable communication. In addition, a network evaluation tool is provided to measure the index of network quality in order to ensure a reliable network quality. In order to evaluate the effectiveness of this tool, we designed a sensor network and simulated the network quality using this tool. The simulation results matched the experimental results of realistic deployment very well.

Pyroelectric infrared (PIR) sensors can detect the presence of human without the need to carry any device, which are widely used for human presence detection in home/office automation systems in order to improve energy efficiency. However, PIR detection is based on the movement of occupants. For occupancy detection, PIR sensors have inherent limitation when occupants remain relatively still. Multisensor fusion technology takes advantage of redundant, complementary, or more timely information from different modal sensors, which is considered an effective approach for solving the uncertainty and unreliability problems of sensing. In this paper, we proposed a simple multimodal sensor fusion algorithm, which is very suitable to be manipulated by the sensor nodes of wireless sensor networks. The inference algorithm was evaluated for the sensor detection accuracy and compared to the multisensor fusion using dynamic Bayesian networks. The experimental results showed that a detection accuracy of 97% in room occupancy can be achieved. The accuracy of occupancy detection is very close to that of the dynamic Bayesian networks.